Targeting IP_6 signaling to destabilize homologous recombination proteins to overcome PARP inhibitor resistance

Domain: neuroscience
Published: 2026-04-04
Editorial outcome: major_revision

Abstract
Homologous recombination (HR) is crucial for maintaining genomic integrity and is tightly
regulated, yet the role of ubiquitin-dependent degradation in HR proteins remains poorly
understood. Through high-throughput screening for compounds that modulate the DNA
replication stress response, we identify ML367 and its derivative, UNI418. Kinase profiling
and detail molecular analyses reveal that UNI418 inhibits PIKfyve and PIP5K1C, reducing
inositol hexaphosphate (IP ) levels and triggering Cul4A-dependent degradation of
6
RAD51, CtIP, and CHK1. Further analysis identifies WDR5 as a DCAF protein that
facilitates Cul4A-mediated proteolysis of RAD51 and CHK1. Functionally, UNI418
suppresses HR, enhances tumor sensitivity to PARP inhibitors (PARPis), and re-
sensitizes PARPi-resistant tumor cells in both in vitrRo and in vivo xenograft models. These
findings reveal a Cul4A-WDR5-dependent proteolysis pathway regulating HR protein
stability via phosphatidyl inositol signaling. TNhis mechanism offers a promising therapeutic
strategy for overcoming PARPi resistance and improving combinatorial cancer treatment
strategies.

Introduction
Genomic instability is a hallmark characteristic of most cancer cells, which is supported
by mounting evidence indicating that impaired DNA repair fosters mutator phenotypes
and chromosomal abnormalities, thereby accelerating cellular transformation 1, 2.
Homologous recombination (HR) is a high-fidelity DNA repair pathway that resolves DSBs
using a homologous DNA template. This process is essential for maintaining genome
stability, particularly during the S and G2 phases of the cell cycle when a sister chromatid
is available 3. RAD51, which is a major recombinase in HR, functions by forming
nucleoprotein filaments on single-stranded DNA (ssDNA) and facilitating strand invasion
into homologous sequences, enabling error-free double-strand break (DSB) repair. Given
its essential role in genome integrity, RAD51 exprRession is tightly regulated at multiple
levels, including transcription, post-transcriptional modifications, and post-translational
mechanisms. RAD51 expression is regulateNd by various transcription factors in response
to DNA damage and cell cycle progression. The tumor suppressor p53 represses RAD51
transcription under genotoxic stress, preventing excessive HR that could lead to genomic
instability 4. E2F1 positively regCulates RAD51 expression, particularly during the S and
G2 phases of the cell cycle, when HR is most active 5. Compared to the well-established
understanding of RADR51 mRNA regulation, the regulation of RAD51 protein levels
remains relatively unexplored. The E3 ubiquitin ligase RFWD3 has been identified as a
ubiquitin ligase that affects both the single-stranded DNA-binding protein RPA and RAD51
on chromatin 6.

Cullin 4A (Cul4A) is a scaffold protein in the CRL4 ubiquitin ligase complex 7, which
includes Damage-Specific DNA Binding Protein 1 (DDB1) and DDB1-CUL4 Associated
Factors (DCAFs). Cul4A plays a crucial role in maintaining genome stability by targeting
key regulatory proteins for ubiquitin-mediated degradation. Dysregulation of Cul4A has
been implicated in various cancers, promoting cell proliferation, genomic instability, and
therapy resistance.

The increased genomic instability observed in cancer frequently originates from
deficiencies in one or more DNA repair pathways, often providing cancer cells with a
selective advantage in advancing toward a more malignant phenotype. These defects
compel cancer cells to rely on the remaining functional DNA repair mechanisms for
survival, particularly considering the heightened proliferation rates 8. Exploiting this
vulnerability presents an opportunity for targeted intervention synthetic lethality
approaches. In this context, inhibiting a key survival DNA pathway becomes lethal upon
inhibition of a redundant pathway 9.

The synthetic lethal approach is particularly successful in targeting BRCA-and other HR-
deficient cancers 10, 11. Mutations in either BRCA1 or BRCA2 predispose individuals to the
development of breast or ovarian cancers, and approximately 10% of breast and 15% of
ovarian cancers are associated with BRCA1 or BRCA2 mutations. The BRCA1 and
BRCA2 proteins play crucial roles in HR, and DNA Rreplication fork protection, and ssDNA
gap suppression 3, 12. Mutations in these genes result in compelling tumor cells to rely on
alternative repair mechanisms which relies oNn PARP1-dependent ssDNA break/gap repair,
replication fork protection, translesion synthesis, or DSB repair 12-16. Inhibition of PARP1
in breast and ovarian cancers with BRCA1 or BRCA2 mutations results in significant cell
death in these tumors while Csparing normal cells 8. The approval of clinically used
PARP1/2-trapping inhibitors (commonly referred to as PARP inhibitors, PARPis), such as
Olaparib, Niraparib, RucRaparib, Veliparib, and Talazoparib, by the US FDA marks a pivotal
advancement of treatment for breast and ovarian cancers carrying BRCA mutations 12.
These inhibitors trap PARP1 at ssDNA breaks or gaps, inducing cell death in HR-deficient
cancer cells 17. However, despite the efficacy of those compounds, tumors often develop
resistance to PARPi 12, 18. This resistance can arise through various mechanisms,
including the restoration of HR including via secondary mutations or BRCA gene
reactivation, re-expression of BRCA expression, or inactivation of DNA damage sensor
proteins such as 53BP1. Additional resistance mechanisms include upregulation of
translesion synthesis and drug metabolism-related processes, such as enhanced drug
efflux 18. There are currently no effective treatment options for PARPi-resistant tumors,
and it is imperative to explore strategies for overcoming resistance to PARPi.

ATAD5 (also known as ELG1 in yeast) is an essential PCNA unloader that maintains
genome stability during DNA replication. Loss or depletion of ATAD5 results in persistent
PCNA retention on chromatin, replication fork stalling, and elevated replication stress,
ultimately contributing to genomic instability and tumorigenesis 19. Importantly, ATAD5-
luciferase expression of the reporter cell line is markedly induced under replication stress,
and this increase has been widely used as an established molecular marker for replication
stress responses 20. In 2010, we reported that a small molecule ML367 selectively
suppresses the elevation of ATAD5-luciferase protein levels in the reporter cell under
replication stress conditions 21.

We have exploited induction of the ATAD5 protein during replication stress as a marker
to screen for compounds that induce replication stress response 22-24. In the current study,
we identified ML367 and its derivative UNI418 as an inhibitory compound of replication
stress response and revealed that they inhibit PIKfRyve and PIP5K1C kinases, leading to
reduced cellular inositol hexaphosphate (IP ) levels and subsequent Cul4A-dependent
6
degradation of RAD51, CHK1 and CtIP, revNealing a mechanism of HR inhibition. We also
found that WDR5 is a DCAF protein of Cul4A determining substrate specificity of Cul4A
to RAD51 and CHK1. Due to the inhibition of key proteins for HR, gap repair, and DNA
replication stress response protCeins, UNI418 induced selective toxicity in PARP1-deficient
or PARPi-resistant cancer cells and tumors in xenograft models. We propose that this
pathway for regulating RHR by the phosphatidyl inositol signaling pathway may provide a
vulnerability for BRCA-deficient tumors.

Results
Identification of a compound, UNI418 that inhibits DNA replication stress response
Our prior investigations revealed that ML367 functions as an inhibitor of the DNA
replication stress responses elicited by 5-fluorouridine (5-FUrd) 21. Subsequent screening
of approximately 100 structurally analogous derivatives of ML367 yielded compounds
with enhanced efficacy in mitigating DNA replication stress. Among these derivatives,
UNI418 was identified as the most effective agent (Fig. 1a,b). The capacity of ML367 and
UNI418 to attenuate DNA replication stress was quantitaStively evaluated utilizing the
ATAD5-luciferase assay (Fig. 1c and Supplementary Fig. 1a). Notably, UNI418
suppressed the 5-FUrd-induced DNA replication stress response more potently than
ML367, as reflected by a lower IC
50
for inhibitioPn of ATAD5 luciferase expression. This
finding is supported by the observed reductions in phosphorylation of RPA32 at serine
residues S4 and S8, as well as CHK1, reIflecting the suppression of the DNA replication
stress response upon treatment witEh ML367 or UNI418 under DNA replication stress
conditions such as camptothecin (CPT), hydroxyurea (HU) and 5-FUrd (Fig. 1d,e and
Supplementary Fig. 1b). InteIrestingly, UNI418 treatment reduced the level of CHK1 as
well as its phosphorylation, even in the absence of DNA replication stress, suggesting it
affects CHK1 expresAsion. In summary, UNI418 is a inhibitory compound of the responses
to DNA replication stress.

UNI418 inhibits PIKfyve and PIP5K1C
Given that UNI418 possesses a core 4-aminoquinazoline moiety—a structural motif
commonly observed in kinase inhibitors 25, known for its affinity towards the ATP binding
pocket—we postulated that UNI418 might exert its biological effects through kinase
inhibition. To elucidate the specific kinase(s) targeted by UNI418, we conducted
comprehensive kinase-profiling analyses using the DiscoverX kinome profiling service
(https://www.discoverx.com/)26. As illustrated in Fig. 2a, kinase profiling analysis reveals
that UNI418 caused the potent inhibition of PIKfyve, a lipid kinase. To verify the result,
we performed PIPK profiling analysis and found that UNI418 inhibited PIP5K1B, PIP5K1C
and PIKfyve 27. The calculated dissociation constant (K ) of PIKfyve and PIP5K1C was
D
0.74 nM, and 61 nM, respectively (Fig. 2b). Notably, a third lipid kinase, PIP5K1B,
demonstrated only partial inhibition under the conditions tested (data not shown). In
kinase-profiling analyses, UNI418 demonstrated inhibitory activity against 11 additional
kinases. Subsequently, we conducted a more detailed assessment of 9 kinases among
them for potential inhibition by UNI418 utilizing Thermo Fisher Scientific's SelectScreen
11-point titration Profiling analysis (Supplementary Fig. 2a). None of them exhibited
inhibition by UNI418 with IC values falling below the 1 nM range (PIKfyve) and only
50
CSF1R, FLT3, and MINK1 exhibited inhibition by UNI418 with IC values falling below
50
the 100 nM range (PIP5K1C). To discern potential off-target effects of UNI418 on these
three kinases as well as BUB1 and GCN2, which wEere not further analyzed through
profiling, we examined the protein levels of CHK1 following knockdown of their expression
(Supplementary Fig. 2b). In contrast to the impact observed with PIKfyve knockdown,
silencing the expression of these kinases did not significantly reduce CHK1 level.

To determine whether UNI418 directly engages with these lipid kinases, we conducted a
surface plasmon resonance (CSPR) analysis. For this purpose, we immobilized the
maltose-binding protein (MBP)-tagged kinase domain of the respective proteins onto a
CM5 chip, a widely utiliRzed platform for ligand immobilization. The purity and integrity of
the recombinant proteins were confirmed by SDS-PAGE analysis (Supplementary Fig.
3a). UNI418 was then injected as an analyte over the chip surface, and changes in
resonance units (RU), which reflect molecular mass accumulation on the sensor surface,
were monitored. Sensorgrams were generated to visualize the interaction kinetics. To
ensure accurate measurement of compound-specific binding, sensorgrams were blank-
subtracted using signals obtained from injections containing DMSO alone at the same
concentration used to solubilize UNI418. This subtraction removed refractive-index
changes and bulk shifts attributable to DMSO, allowing the binding response induced
specifically by UNI418 to be assessed. The blank-subtracted sensorgram data
unequivocally demonstrated the direct interaction of UNI418 with both PIKfyve and
PIP5K1C, corroborating the findings regarding UNI418's inhibitory activity against these
lipid kinases (Fig. 2c). There was minimal interaction between UNI418 and MBP, which
was fused to the kinases used in this study for purification (Supplementary Fig. 3b). We
sought to observe evidence for the interaction of UNI418 with the two kinases, PIKfyve
and PIP5K1C in cells. To achieve this, we employed the cellular thermal shift assay
(CETSA), a technique designed to measure the stabilization of a protein to heat
denaturation upon ligand binding 28. We treated cell lysates with either UNI418 or DMSO
and subjected them to varying temperatures. The presence of the target proteins in the
soluble fraction was then analyzed using western blotting. Our results revealed that after
treatment with UNI418, ectopically expressed PIKfyve and PIP5K1C exhibited increased
stability at higher temperatures than the DMSO (Fig. 2d). This observation suggests that
UNI418 interacts with PIKfyve and PIP5K1C within cellular environments, corroborating
our in vitro findings.

UNI418 reduces the level of phosphorylated inositol species in cells
Lipid kinases, including PIKfyve and PIIP5K1C, play crucial roles in phosphorylating
inositol-containing molecules, which Eare integral to various cellular signaling pathways as
second messengers 29, 30. Specifically, PIKfyve phosphorylates PI(3)P to produce
PI(3,5)P
2,
while PIP5K1C caItalyzes the phosphorylation of PI(4)P and PI(3,4)P
2
to
generate PI(4,5)P and PI(3,4,5)P , respectively (Fig. 2e) 31.
2 R 3

In our investigation, we initially assessed the levels of phosphoinositides following UNI418
treatment using the phosphoinositides analysis service in the Creative Proteomics
Lipidomics (https://lipidomics.creative-proteomics.com/). Notably, the PIP, PIP , and PIP
2 3
levels were all reduced upon treatment with UNI418 or the PIKfyve inhibitor Apilimod
(Supplementary Fig. 4a). Given that PI(4,5)P is enzymatically cleaved by phospholipase
2
C to generate I(1,4,5)P , which is subsequently phosphorylated to form more
3
phosphorylated inositol species including I(1,2,3,4,5,6)P (IP ), also known as inositol
6 6
hexaphosphate 32, we hypothesized that UNI418 may inhibit IP
6
production, which has
been linked to the regulation of CHK1 protein level 33. Consistent with our hypothesis,
UNI418 treatment, as well as Apilimod or UNC3230, which inhibits PIKfyve and PIP5K1C,
respectively, resulted in a reduction of IP as well as IP , IP ,and IP in cells (Fig. 2f and
6 3 4 5
Supplementary Fig. 4b,c).

To identify the interaction residues of PIKfyve and PIP5K1C with UNI418, we modeled
their potential interactions. We identified two possible interaction pockets in both PIKfyve
and PIP5K1C: one in ATP binding pocket and the other predicted binding pocket using
RosettaDock and AutoDock programs, respectively (Supplementary Fig. 5a) 34, 35. To
determine which pocket interacts with UNI418, we introduced amino acid substitutions in
these regions. The purified mutant proteins were analyzed using CETSA to assess their
interaction with UNI418. The ATP-binding pocket mutation (ABM) in PIKfyve (ABM1,
L2020A) disrupted its interaction with UNI418, whereas the wild-type (WT) protein and
other mutants—ABM2 (I2875A, K1877A), predicted binding pocket mutation (PBM)1
(D1951A), and PBM2 (K1953A, R1959A)—retained their interaction with UNI418
(Supplementary Fig. 5b). Similarly, in PIP5K1C, the ABEM1 mutation (L320A) abolished its
interaction with UNI418, while the WT protein and other mutants, ABM2 (O186A, K188A)
still interacted with UNI418 (Supplementary Fig. 5c). Collectively, these results indicate
that UNI418 interacts with both PIKfyve and PIP5K1C through their ATP-binding pockets.
This result aligns with the presence of a core 4-aminoquinazoline moiety in UNI418, which
is known to interact with ATP-bindiLng pockets 25.

UNI418 treatment down-regulates the level of RAD51 and CtIP as well as CHK1 and
inhibits HR R

Unexpected downregulation of CHK1 protein by UNI418 treatment, along with reduced
CHK1 phosphorylation in response to DNA replication stress (Fig. 1d and Supplementary
Fig. 1b), suggests that inhibiting PIKfyve and PIP5K1C may activate proteasomal
degradation of CHK1. Previous study has shown that Cul4A plays a role in ubiquitinating
various proteins in response to DNA damage and regulating CHK1 protein levels 33. To
explore this further, we investigated whether UNI418 downregulates CHK1 protein by
activating proteolysis. First, we examined whether UNI418 treatment affects the levels of
other DSB repair-associated proteins. In addition to CHK1, we found that RAD51 and
CtIP levels were also reduced following UNI418 treatment (Fig. 3a and Supplementary
Fig. 6a). BRCA1 level was also mildly reduced upon UNI418 treatment. This reduction
was not observed in other DSB repair proteins such as MRE11, Ku80 and DNA-PKcs.
CtIP and RAD51 are essential for HR, with CtIP initiating DNA end resection to generate
ssDNA tails required for HR. RAD51 binds to the resected ssDNA to form a nucleoprotein
filament that facilitates homology search and strand invasion. Upon ionizing radiation (IR)-
induced DSBs, CtIP and RAD51 rapidly localize to damage sites 36. To assess the impact
of UNI418 on HR efficiency, we examined CtIP and RAD51 accumulation at DNA
damage-induced foci following IR exposure. After 10 Gy IR, RAD51 and CtIP formed
distinct nuclear foci that co-localized with the DNA damage marker γH2AX. However,
UNI418 treatment significantly reduced RAD51 foci formation and overall nuclear RAD51
intensity (Supplementary Fig. 6b), as well as CtIP foci formation (Supplementary Fig. 6c)
correlating with decreased protein levels (Fig. 3a and Supplementary Fig. 6a). These
results suggest that UNI418 downregulates HR efficieEncy.

To further investigate the mechanism underlyiPng UNI418-mediated HR inhibition, we
analyzed the distribution and abundance oNf RAD51, CHK1, and CtIP in chromatin and
soluble fractions following hydroxyureaI (HU) treatment, with and without UNI418
(Supplementary Fig. 6d). UNI418 reduced RAD51, CHK1, and CtIP protein levels in both
soluble and chromatin fractions.

Proteolysis mediates this reTduction, as co-treatment with the proteasome inhibitor MG132
restored RAD51, CHK1, and CtIP levels (Fig. 3c). Notably, UNI418 treatment did not alter
RAD51, CHK1, and CtIP mRNA levels, indicating that it specifically affects protein stability
rather than transcriptional regulation (Supplementary Fig. 6e). Protein degradation
kinetics studies using cycloheximide (CHX) chase experiment further confirmed that
UNI418 accelerates HR protein degradation compared to control cells (Fig. 3d).

Previously, inositol polyphosphate multikinase (IPMK) has been identified as a key
regulator involved in modifying I(1,4,5)P to I(1,3,4,5)P , and subsequently to
3 4
I(1,3,4,5,6)P . Notably, IPMK has been implicated in the regulation of nuclear export of
5
RAD51 mRNA 37. To investigate whether UNI418 influences RAD51 mRNA export, we
isolated nuclear and cytoplasmic mRNA fractions from RPE1 cells treated with UNI418.
Upon UNI418 treatment, we observed no significant alteration in the cytoplasmic levels
of RAD51, CHK1, and CtIP mRNAs, while a modest increase in CHK1 and CtIP mRNA
levels was detected in the nuclear fraction (Supplementary Fig. 7a). Furthermore,
assessment of mRNA localization using RAD51 RNA fluorescence in situ hybridization
(FISH) revealed no significant perturbation upon UNI418 treatment (Supplementary Fig.
7b). These results collectively suggest that UNI418 does not inhibit RAD51 mRNA
transport, thus excluding this mechanism as a mode of action for UNI418 in regulating
RAD51 expression.

Next, we investigated whether HR frequency would be affected by UNI418 treatment. We
employed DSB repair reporter assays designed to quantitatively assess HR and non-
homologous end joining (NHEJ) repair pathways. These assays utilize a GFP-based
readout to signal successful DSB repair via HR or NHEJ following targeted cleavage by
the I-SceI restriction endonuclease 38. UNI418 treatment significantly reduced HR repair,
with only a marginal impact on NHEJ repair (Fig. 3e). Notably, this reduction in HR
frequency was less pronounced than that observed upon siRAD51-mediated knockdown,
consistent with the partial reduction of NRAD51 protein levels induced by UNI418
(Supplementary Fig. 7c).

Lastly, we investigated whether UNI418 would cause cells sensitive to PARP1 deficiency
and PARPi, Olaparib. We detIermined the IC
50
of UNI418 for selectively targeting PARP1-
deficient cells. We subjected colorectal tumor HCT116 cells and their isogenic
counterparts lackingA PARP1 (HCT116 PARP1-/- cells, generated via targeted gene
deletion, Supplementary Fig. 7d) to varying concentrations of UNI418 and measured
cellular survival. Notably, the IC values of UNI418 in HCT116 and HCT116 PARP1-/-
50
cells were measured at 1.65  0.23 μM and 0.44  0.04 μM, respectively (Fig. 3f).
Furthermore, treatment with UNI418 induced a greater extent of apoptotic cell death in
HCT116 PARP1-/- cells compared to their WT (Fig. 3g).

To examine the basis of this dose-dependent hypersensitivity, we performed dose-
response analyses of UNI418 (0 to 5 μM) and assessed the levels of RAD51, CHK1, CtIP,
Cul4A and H2AX in both cell types. HR-associated proteins exhibited a gradual, dose-
dependent reduction in WT cells, whereas PARP1-/- cells showed a more rapid and
pronounced decrease at lower UNI418 concentrations (Supplementary Fig. 8a). In
parallel, H2AX accumulation was markedly enhanced in PARP1-/- cells relative to WT
cells. These results indicate that the heightened sensitivity of PARP1-deficient cells to
UNI418 arises from their increased reliance on HR for genome maintenance, rather than
from nonspecific off-target toxicity.

Consistent with the enhanced efficacy of UNI418 against PARP1-/- cells, we also observed
a synergistic cytotoxic effect of UNI418 when combined with the PARPi, Olaparib in
HCT116 WT cells, resulting in increased apoptotic cell death (Fig. 3h,i and Supplementary
Fig. 8b). The increased concentration of Olaparib exhibited a combination index lower
than 1, as determined by the CompuSyn algorithm 39, indicating synergism
(Supplementary Fig. 8c).

Collectively, these findings suggest that UNI418 promotes proteolytic degradation of
RAD51, CHK1, and CtIP, impairing HR repaPir mechanisms resulting in enhanced
cytotoxicity in PARP1 inhibition condition.

PIKfyve and PIP5K1C inhibition down -regulates HR
To determine that PIP5K1C andC PIKfyve, the lipid kinases inhibited by UNI418, are indeed
responsible for mediating the UNI418-induced proteasomal degradation of RAD51, CHK1,
and CtIP, we conducteRd experiments involving the knockdown of these kinases using
siRNA. Upon treating cells with siRNA targeting PIP5K1C or PIKfyve, we observed a
significant reduction in the protein levels of RAD51, CHK1, and CtIP, akin to the effects
induced by UNI418 treatment (Fig. 4a,b). UNI418 treatment did not further decrease the
levels of RAD51, CHK1 and CtIP under PIKfyve knockdown conditions. Notably, the
knockdown of PIP5K1B did not elicit substantial changes in the levels of RAD51 or CHK1
proteins. Furthermore, consistent with the observed reductions in HR proteins, HR
efficiency was significantly diminished upon knockdown of PIP5K1C and PIKfyve, but not
PIP5K1B (Fig. 4c).

We next examined whether inhibition of PIP5K1C and PIKfyve influences cellular
sensitivity to the PARP inhibitor Olaparib. Cells depleted of either kinase exhibited
increased sensitivity to Olaparib compared with control cells, and dual depletion of both
kinases resulted in a more pronounced reduction in cell viability, indicating an additive
effect between PIP5K1C and PIKfyve (Fig. 4d). Under the CellTiter-Glo viability assay
following 72 h Olaparib treatment, BRCA2 knockdown cells also showed increased
sensitivity to Olaparib, with a reduction in viability similar in scale to that observed upon
combined depletion of PIP5K1C and PIKfyve. Notably, clonogenic survival assays
performed with extended Olaparib exposure showed substantially stronger
hypersensitivity in BRCA2-depleted cells, consistent with canonical HR-deficient
phenotypes (Supplementary Fig. 8d).

Importantly, UNI418 treatment alone reduced cell viability to a similar extent as single or
combined knockdown of PIP5K1C and PIKfyve, and no additional reduction was
observed upon further kinase depletion (Fig. 4e). This lack of additivity indicates that
UNI418 and genetic depletion of PIP5K1C and PIKRfyve act through the same functional
pathway, supporting a shared mechanism involving inhibition of PIP5K1C and PIKfyve
activity.

Together, these findings suggest thaEt UNI418 exerts its effects on RAD51, CHK1, and
CtIP through the inhibition of PIKfyve and PIP5K1C. The observed reductions in HR
proteins and HR efficiency upIon knockdown of these kinases, as well as the increased
sensitivity to Olaparib upon their depletion, underscore the crucial role of PIKfyve and
PIP5K1C in mediatinAg UNI418-induced effects on DSB repair and cellular response to
DNA damage.

Reduction of IP level regulates Cul4A-dependent proteolysis of HR proteins
6
Cul4A is an E3 ubiquitin ligase that facilitates the degradation of target proteins. Its activity
is tightly controlled by neddylation, a post-translational modification that enhances its
ability to recruit substrate adaptors and promote ubiquitination 40. A previous study has
shown that Cul4A plays a role in ubiquitinating various proteins in response to DNA
damage including CHK1 33. We explored the possibility of Cul4A for proteasomal
degradation of RAD51, CHK1, and CtIP in response to UNI418 through IP level change.
6
UNI418 treatment increased the ratio of neddylated Cul4A to unneddylated Cul4A (Fig.
5a). Conversely, supplementation with IP both in cells or extracts, counteracted the
6,
UNI418-induced Cul4A neddylation (Fig. 5a and Supplementary Fig. 9a). Furthermore,
the depletion of PIP5K1C and PIKfyve, akin to UNI418 treatment, increased the ratio of
neddylated Cul4A (Fig. 5b). Importantly, neither UNI418 treatment nor knockdown of
PIKfyve or PIP5K1C led to an increase in the absolute level of neddylated Cul4A. Instead,
both procedures augmented the ratio of neddylated Cul4A to unneddylated Cul4A, as
observed in previous studies 41. This observation suggests that the unneddylated form of
Cul4A may potentially play an inhibitory role in neddylated Cul4A, or that neddylated
Cul4A quickly ubiquitinates its substrate, leading to turnover.

To address whether Cul4A can directly regulate HR proteins such as RAD51 and CtIP,
we investigated the impact of Cul4A depletion on the levels of RAD51, CHK1 and CtIP in
the presence or absence of UNI418. Upon depleRtion of Cul4A using siRNA, RAD51,
CHK1, and CtIP levels increased compared to control cells (Fig. 5c). In contrast, their
level increase was less pronounced under NUNI418 treatment conditions. These findings
suggest that Cul4A is responsible for the degradation of RAD51, CHK1 and CtIP upon
UNI418 treatment. Furthermore, supplementation of cells with IP antagonized UNI418-
6
induced HR protein degradatioCn and promoted RAD51 foci formation upon IR treatment
(Fig. 5a,e and Supplementary Fig. 9b). UNI418-mediated reduction in HR frequency was
also restored upon addiRtional supplementation of IP (Fig. 5e). Moreover, in the presence
6
of IP , the hypersensitivity of PARP1-/- cells to UNI418 was fully suppressed, indicating
6
that reducing IP levels is a key contributor to the HR defects induced by UNI418
6
(Supplementary Fig. 9c). However, it is important to note that IP exhibited toxicity in both
6
WT and PARP1-/- cells.

Inositol-pentakisphosphate-2-kinase (IPPK) plays a pivotal role in catalyzing the
conversion of IP to IP . To elucidate whether UNI418 is primarily acts by a reduction in
5 6
IP levels, we anticipated that depletion of IPPK would phenocopy the effects induced by
6
UNI418. Indeed, upon depletion of IPPK using siRNA (Supplementary Fig. 9f), we
observed a reduction in the levels of HR proteins even in the absence of UNI418
treatment (Supplementary Fig. 9d). Moreover, IPPK-depleted cells exhibited heightened
sensitivity to Olaparib, mirroring the phenotype observed upon UNI418 treatment
(Supplementary Fig. 9e).

WDR5 is a DCAF of Cul4A for proteolysis of RAD51and CHK1
Cul4A substrate specificity is determined by its interacting proteins, known as DCAFs.
With over 60 predicted DCAFs 42, we aimed to identify the one responsible for RAD51
proteolysis. To this end, we screened available siRNAs targeting DCAF genes and
monitored RAD51 and CHK1 levels. Among them, WDR5 silencing consistently increased
RAD51 and CHK1 levels (Fig. 6a). In contrast, WDR5 knockdown did not increase CtIP
levels, which suggest CtIP is regulated by other DCAF. Additional proteasome inhibition
using MG132 showed further enhancement of the observed effects, suggesting that
residual protein levels due to incomplete knockdown of WDR5 and Cul4A may have
masked the full recovery of RAD51 and CHK1. Consistent with the role of WDR5 as a
potential DCAF for Cul4A, the simultaneous silenciRng of Cul4A and WDR5 did not further
elevate RAD51 and CHK1 levels. However, while WDR5 knockdown increased RAD51
and CHK1 levels, its overexpression did noNt result in a corresponding decrease (Fig. 6b).

The substrate of an E3 ubiquitin ligase transiently interacts with its E3 ligase 43. We
examined the potential interaction between RAD51 and CHK1 with WDR5. In the
presence of the proteasome inChibitor MG132, WDR5 was able to pull down RAD51 and
CHK1 as well as Cul4A and its interacting partner, DDB1 (Fig. 6b). To assess whether a
slight increase in RAD5R1 and CHK1 levels influences sensitivity to PARPi, cell survival
was measured following exposure to a high concentration of Olaparib after silencing
WDR5, Cul4A or both. Silencing of WDR5, Cul4A, or their combination conferred
resistance to Olaparib. (Fig. 6c). Collectively, we identified WDR5 as a key determinant
of RAD51 and CHK1 proteolysis through Cul4A, highlighting its regulatory role in HR.

Previously, RFWD3 was identified as an E3 ligase that facilitates the degradation of
RAD51 following the completion of HR 6. To determine whether both RFWD3 and Cul4A
contribute to RAD51 proteolysis, we assessed RAD51 levels upon siRNA-mediated
depletion of RFWD3 (Supplementary Fig. 9g) and Cul4A, individually and in combination.
Silencing Cul4A resulted in increased RAD51 levels under both basal and IR-induced
conditions (Fig. 6d). In contrast, RFWD3 depletion led to RAD51 accumulation exclusively
in response to IR. Notably, co-silencing RFWD3 and Cul4A did not further augment
RAD51 levels beyond those observed upon individual knockdowns. These findings
suggest that Cul4A governs RAD51 homeostasis under normal physiological conditions,
whereas RFWD3 primarily mediates RAD51 degradation in response to DNA damage.

UNI418 inhibits tumor growth in PARP1-deficient tumors and enhances the efficacy
of PARPi in combination therapy
Building on the premise that UNI418's superior efficacy in killing PARP1-deficient cells
and its synergistic effect with PARPi in vitro (Fig. 3g,h,i,j) could translate into effective in
vivo antitumor activity, we conducted a series of tumor xenograft experiments. To this end,
we implanted either WT or PARP1-/- HCT116 cancer Scells into male NOD.CB17-
Prkdcscid/J mice to generate xenograft tumors. Upon the t S umors reaching an approximate
diameter of 0.5 cm, we administered 4 ml/kg of vehicle or 10 mg/kg of UNI418 directly
into the tumors every other day for a durationP of 12 days. Consistent with our initial
hypothesis, the application of UNI418 markedly suppressed tumor growth exclusively in
the PARP1-/- xenografts, with no significaInt effect observed in the WT tumors (Fig. 7a).
Notably, the co-administration of 50 mEg/kg Olaparib with 10 mg/kg UNI418 resulted in the
inhibition of HCT116 tumor growth, an outcome not achieved with either agent alone (Fig.
7b). Importantly, there was Ino significant alteration in the body weights of the mice
throughout the treatment period, irrespective of whether placebo or active drug treatment
was used (SupplemAentary Fig. 10a). The pharmacokinetic data of UNI418 was not yet
applicable for therapeutic use suggesting the need for further development for clinical
application (Supplementary Fig. 10b). These findings collectively underscore the potential
of UNI418, particularly in conjunction with Olaparib, as a promising therapeutic strategy
against cancers harboring PARP1 deficiencies and possibly extending to broader
applications in other tumor types.

UNI418 kills Olaparib-resistant ovarian cancer cells
Ovarian and breast tumors deficient in BRCA1 or BRCA2 are known to exhibit sensitivity
to PARPi such as Olaparib 8. Nonetheless, the therapeutic management of these
malignancies frequently culminates in the development of PARPi-resistant tumors, posing
a significant challenge to effective clinical outcomes. In this context, PEO-1 and Capan-1
cell lines, derived from BRCA2-deficient ovarian adenocarcinoma and pancreatic ductal
adenocarcinoma respectively, demonstrated susceptibility to PARPi treatment (Fig. 7c,f).
However, C4-2 and C2-2 clones, which originated from PEO-1 and Capan-1 cells,
respectively and harbor a reversion mutation in the BRCA2 gene, exhibited resistance to
PARPi, underscoring a pivotal mechanism of therapeutic evasion 44, 45. Given the
established selectivity of UNI418 for PARP1-/- cells (Fig. 3g,h), we posited that UNI418
might effectively target PARPi-resistant cancer cells, thereby re-sensitizing tumors that
have acquired resistance through BRCA2 reversion mutations to PARPi therapy. In
alignment with our hypothesis, the PARPi-resistant clones C4-2 and C2-2 displayed
enhanced sensitivity to UNI418 in comparison to their parental PEO-1 and Capan-1
counterparts (Fig. 7d,g). Moreover, co-administraEtion of UNI418 with Olaparib
significantly augmented the sensitivity of the PARPi-resistant C4-2 and C2-2 cells to
Olaparib, relative to treatment with Olaparib alone in the parental cell lines (Fig. 7e,h and
Supplementary Fig. 11). Crucially, this increase in drug sensitivity was paralleled by a
marked elevation in apoptotic cell death among the PARPi-resistant C4-2 cells following
UNI418 treatment (Fig. 7i). TheLse findings collectively suggest that UNI418 holds
considerable promise as a therapeutic agent capable of overcoming one of the common
pathways of acquired resisTtance to PARPi therapy of BRCA-deficient tumors.

In summary, our findings reveal that UNI418 exerts its effects by inhibiting PIKfyve and
PIP5K1C to reduce IP levels. This reduction in IP levels enhances Cul4A neddylation,
6 6
consequently activating the E3 ligase pathway. Activated Cul4A initiates the degradation
of HR proteins, ultimately leading to HR defects. In particular, the major recombinase
RAD51 and CHK1 are targeted by Cul4A with its specificity determined by a DCAF, WDR5.
Importantly, these HR defects render PARPi-resistant cells hypersensitive to UNI418
treatment. This comprehensive understanding of the molecular mechanisms underlying
UNI418's action provides valuable insights into its potential therapeutic applications for
treating PARPi-resistant cancers (Fig. 7j).

Methods
The abbreviations used in this study and their full names are provided in Supplementary
Table 1.

Cell culture
HCT116 (from Eric Hendrickson’s lab), HCT116 PARP1-/- (generated in our lab) HEK293T
(ATCC), RPE1 (Medical College of Georgia), U2OS (ATCC), PEO-1 (Toshiyasu
Taniguchi’s lab), C4-2 (Toshiyasu Taniguchi’s lab), Capan-1 (Toshiyasu Taniguchi’s lab)
and C2-2 (Toshiyasu Taniguchi’s lab) cells were cultured in Dulbecco’s modified Eagle’s
medium (DMEM) containing 10% fetal bovine serum (GEE Healthcare, Little Chalfont, UK),
100 U/mL penicillin G (Life Technologies, Carlsbad, CA) and 100 μg/mL streptomycin (Life
Technologies). RPE1 cells were cultured in DMEM/F12 containing 10% feta bovine serum,
100 U/mL penicillin G and 100 μg/mL streptomycin.

Chemicals
The following chemicals were pCurchased from Sigma-Aldrich: HU (Sigma-Aldrich, H8627),
5-FUrd (Sigma-Aldrich, F5130), MG132 (Sigma-Aldrich, C2211-5mg) ATRi (VE821,
SML1415) and IP
6
(Sigma-Aldrich, 593648). Olaparib was purchased from Selleckchem.
ML367 and UNI418 were synthesized in the laboratory as previously described 27.

Luciferase assays
3 x 105 HEK293T Luc-ATAD5 cells 22 were plated in each well of 6 well culture plates and
incubated to attach to the bottom of the plate for 24 hours. Cells were then treated with
indicated chemicals for 24 hours. Cells were harvested, and luciferase activity was
measured using the Dual-Luciferase® Reporter Assay System (Promega, E1910). The
luminescence was determined using Synergy NEO2 Hybrid Multi-Mode Reader (Biotek).

Western blot analysis
Whole-cell extracts were prepared by lysis of harvested cells with M-PER Mammalian
protein extraction reagent (Thermo). Protein concentrations were determined by the
Bradford protein assay (Bio-Rad). 20 to 30 μg of prepared proteins were separated by
the SDS-PAGE and transferred to a nitrocellulose membrane, which was then blocked in
5% skim milk at room temperature for 30 minutes. Membranes were incubated with a
primary antibody detecting the protein of interest at 4°C overnight. After washing with Tris-
Buffered Saline (TBS) with 0.05% Tween (TBS-T), the membranes were incubated with
a secondary antibody at room temperature for one hour. The images were detected by
the Odyssey imaging system (Li-COR Biosciences) or ChemiDoc (Bio-Rad).

Antibodies
The following antibodies were used for western blotting and immunofluorescent staining;
Rabbit polyclonal RAD51 (CST, #8875, 1:1000), phosEphorylated RPA32 at Serine 4 and
8 (Bethyl, A300-245A, 1:1000), histone H3 (Millipore, #07-690, 1:1000), CtIP (CST,
#9201S, 1:1000), GAPDH (abcam, ab181603, 1:1000), Cul4A (CST, #2699, 1:1000),
PIP5K1C (CST, #3296, 1:1000), HSP90 (CST, #4874S, 1:1000) and GFP (abcam,
ab32146, 1:1000). Mouse monoclonal C HK1 (CST, #2360, 1:1000), α-tubulin (SantaCruz,
sc-32293, 1:1000), β-actin (SigmLa-Aldrich, A3853, 1:1000), WDR5 (CST, #13105S,
1:1000), PIP5K1B (SantaCruz, sc-514169, 1:1000) and PIKfyve (Millipore, MABS522,
1:1000). The anti-human TATAD5 antibody was raised in rabbits using the N-terminal
fragment (residues 1–297 amino acids) 19 and was used at a dilution of 1:1000.

SelectScreen kinase assay
Kinase assays were performed using the SelectScreen® Kinase Profiling platform
(Thermo Fisher Scientific). Kinase-tagged T7 phages were produced in an E. coli BL21-
derived host, and additional kinases were expressed in HEK293 cells and subsequently
DNA-tagged for qPCR detection. Streptavidin-coated magnetic beads were incubated
with biotinylated small-molecule ligands to generate affinity resins, followed by blocking
with buffer to minimize nonspecific binding. Binding reactions were assembled by mixing
kinases, ligand-coupled beads, and test compounds in binding buffer (20% SeaBlock,
0.17 PBS, 0.05% Tween-20, 6 mM DTT). Test compounds were applied as an 11-point
3-fold serial dilution series, with a final DMSO concentration of 0.9%. Reactions were
carried out in 384-well plates at a final volume of 20 µL and incubated for 1 h at room
temperature. Beads were then washed and resuspended in elution buffer containing 0.5
µM non-biotinylated ligand. The concentration of eluted kinases was quantified by qPCR,
and dissociation constants (K ) were determined from concentration–response curves.
D

Surface Plasmon Resonance (SPR)
SPR experiment used a Biacore T200 instrument. 10 mg/ml of purified proteins were
diluted in 10 mM sodium acetate, pH5.0. and immobilized in a CM5 chip (GE Healthcare)
using standard amine coupling. HBS-EP+ buffer, which consisted of 0.1 M HEPES, 1.5
M NaCl, 0.03 M EDTA, and 0.5% v/v Surfactant P20, was used as a running buffer. After
immobilizing the protein, UNI418 was diluted into the PBS-P20 with 5% DMSO solution
to create a series of concentrations. UNI418 was inEjected into the channels, and the
binding responses were recorded in RU.

Cloning, protein expression, and purificNation
The gene encoding the kinase domain of human PIKfyve and PIP5K1C was amplified
from GFP-hPIKfyve and GFP-PIPKL1 gamma 90 (GFP-PIP5K1C) plasmid purchased from
Addgene (#121148, #22299) and cloned into expression vector pVFT4S which contains
a poly-histidine tag, a maltTose binding protein (MBP) tag and a tobacco etch virus (TEV)
protease recognition site. The plasmid was transformed into Escherichia coli strain BL21
(DE3) Codon Plus cells. Cells were grown at 37°C until OD reaches 0.8 in LB media
600
containing 50 mg/ml kanamycin and 0.5 mM isopropyl β-D-thiogalactopyranoside (IPTG)
was added. Cells were further cultured at 15°C for 15 hours. Grown cells were harvested
by centrifugation at 7,500 x g for 10 minutes. Collected pellets were resuspended in lysis
buffer (20 mM Tris-HCl pH7.3, 300 mM NaCl, 5% glycerol, 0.5% Triton X-100) and
disrupted by sonication. The lysate was pelleted by centrifugation at 36,000 x g for one
hour. Cell debris was removed, and the supernatant was loaded on amylose resin (NEB),
and bound proteins were eluted with 20 mM maltose. Eluted proteins were diluted to a
final salt concentration of 50 mM NaCl, then purified using an anion exchange column
(HiTrap Q HP, 1 x 5 ml, GE Healthcare Life Sciences) equilibrated with 20 mM Tris-HCl
pH7.3, 50 mM NaCl, 2.5% glycerol, 0.03% Triton X-100 in an ÄKTA prime plus device
(GE Healthcare Life Sciences). Protein elution was performed with a salt gradient from
50 mM to 1 M NaCl. Further purification was proceeded using a HiLoad 16/600 Superdex
200 prep-grade column in an ÄKTA purifier (GE Healthcare Life Sciences) with storage
buffer (20 mM Tris-HCl pH7.3, 300 mM NaCl, 2.5% glycerol). The plasmid expressing full
length WDR5 was obtained from Addgene (#29759 and #59974).

Cellular Thermal Shift Assay (CETSA)
HEK293T cells were treated with 5 μM UNI418 for 1 h prior to harvesting. Cells were
collected, washed with PBS, and resuspended in PBS. Equal volumes of the cell
suspension were aliquoted into microcentrifuge tubes and heated to the indicated
temperatures for 3 min to denature and precipitate target proteins. Heated samples were
immediately snap-frozen in liquid nitrogen. After two fEreeze–thaw cycles, the tubes were
briefly vortexed, and the resulting cell lysates were subjected to SDS–PAGE.

High Performance Liquid ChromatograpNhy for detection of inositol phosphates
For HPLC analysis, 1 x 105 cells/60mm dish of RPE-1 (human retinal pigment epithelial
cell) were treated with 60 μCi [3HL] myoinositol (NET1177001MC, PerkinElmer). After 3
days, soluble inositol polyphosphates from RPE-1 were extracted and analyzed.
Intracellular inositol phospThates were extracted with acid extraction buffer (1 M HClO , 3
4
mM EDTA and 0.1 mg/ml IP ) and neutralized with neutralization buffer (1 M K CO and
6 2 3
3 mM EDTA). The lysates were centrifuged for 10 minutes, and a soluble fraction was
resolved by HPLC. Lipid pellets were lysed with 0.1 % Triton X-100 in NaOH for overnight.
Each fraction was mixed with Ultima-Flo AP liquid scintillation cocktail (6013599,
PerkinElmer), and radioactivity was counted in the scintillation counter. The quantity of
inositol phosphates was presented as total counts/min (CPM) normalized by total lipid
contents or inositol counts.

Immunofluorescence and EdU labeling
RPE1 cells were plated on an 8-well chamber slide (Lab-Tek) and incubated for one day.
The cells were treated with or without 0.5 μM UNI418 for 18 h and pulsed with 10 μM EdU
for 20 minutes prior fixation to label S-phase cells. To visualize chromatin-bound proteins
by immunofluorescence, chemical-treated cells were washed with PBS and
permeabilized with CSK buffer (10 mM PIPES (pH6.8), 100 mM NaCl, 300 mM Sucrose,
3 mM MgCl , 1 mM EGTA (pH7.5)) with 0.5% Triton X-100 at room temperature for 10
2
minutes. The cells were fixed with 4% paraformaldehyde, followed by incubation in 100%
methanol at -20°C for 10 minutes. After fixation, EdU incorporation was detected using
the Click-iT EdU imaging kit according to the manufacturer’s instructions. Cells were
subsequently blocked with 5% FBS and incubated with primary antibodies at 4°C
overnight. Following three washes with PBS containing 0.1% Tween 20 (PBS-T), cells
were incubated with fluorescence-conjugated secondary antibodies (Invitrogen) at room
temperature for 1 hour. Nuclei were counterstained with DAPI using permanent mounting
medium (Vector Laboratories). Images were acquired using an LSM 880 confocal
microscope (Carl Zeiss). For experiments involving EdEU labeling, only EdU-positive nuclei
were included in downstream quantitative analyses, as indicated in the figure legends.

Determination of DNA DSB repair frequeNncy
To evaluate DNA DSB repair frequenEcy, GFP-reporter assays were performed. U2OS cell
lines stably integrated with reporter constructs (DR-GFP for HR and EJ5-GFP for NHEJ,
from Dr. Jeremy Stark) were uIsed, as previously described 73. For the assay, 5 × 10⁴ cells
were seeded in 1 ml of complete media in a 12-well plate. After 12 hours, cells were
transfected with 0.5 µg of the I-SceI expression plasmid (pCAG-I-SceI) using 3 µl of
Lipofectamine 3000 (Invitrogen) in 0.1 ml of antibiotic-free medium. Six hours post-
transfection, the media was replaced with fresh medium containing UNI418. GFP-positive
cells were quantified by flow cytometry using a Becton Dickinson FACSVerse two days
post-transfection.

Cell viability assays
4 x 103 cells plated in each 96 well were treated with chemicals at the indicated
concentration for 72 hours. Cell viability was measured using a CellTiter-Glo assay kit
(Promega) following the manufacturer’s protocol. The absorbance was determined at
luminescence using Synergy NEO2 Hybrid Multi-Mode Reader (Biotek).

Annexin V/ PI staining assays
Cells were harvested and re-suspended with Annexin-binding buffer. Re-suspended cells
were immediately incubated with Annexin V- Alexa FlourTM 488 and propidium iodide at
room temperature for 15 minutes. Apoptotic cells were analyzed using Becton Dickinson
FACSVerse.

siRNA
All siRNA oligonucleotides were purchased from Bioneer, Genolution or Sigma-Aldrich.
These siRNAs were transfected into the cell using lipofectamine RNAiMAX (Invitrogen)
following manufacturer’s protocol. The sequences of the siRNAs are provided in
Supplementary table 3.

Immunoprecipitation
HCT116 cells were transfected with vectors e ncoding FLAG-WDR5 24 hours. MG132
(Sigma Aldrich, C2211-5mg) 10 μM was treated 3 hours and cells were harvested 24
hours after transfection. Whole-cell lys ates were prepared by lysing cells with buffer X
(100 mM Tris-HCl (pH 8.5), 250 mLM NaCl, 1 mM EDTA, 1 % NP40, and 5 mM MgCl )
2
supplemented with the Protease and Phosphatase Inhibitor Cocktail (Thermo Fisher
Scientific), and 50 units Tof Benzonase for 1 hour at 4°C. Lysates were cleared by
centrifugation (15,000 x g, 4°C, 10 minutes). FLAG-tagged proteins were incubated with
anti-FLAG M2 agarose affinity beads (Sigma Aldrich) for 1 hour at 4°C with constant
rotation. The beads were washed three times using buffer X, and anti-FLAG bead-bound
proteins were eluted with buffer X containing 0.15 mg/ml FLAG peptide.
Coimmunoprecipitated proteins were loaded onto SDS-PAGE and analyzed by
immunoblotting. The proteins were detected by means of a ChemiDoc MP imaging
system (Bio-Rad).

Mice experiments
Six weeks old NOD.CB17-Prkdcscid/J male mice were purchased from the Orientbio. Mice
were housed under specific pathogen-free condition with a 12 hours light and 12 hours
dark cycle at an ambient temperature of 22 ± 2°C and a relative humidity of 40-60%. To
induce subcutaneous human colon cancer xenografts, 1 x 106 HCT116 PARP1+/+ or
PARP1-/- cells in 200 µl of 50% Matrigel (#354234, Corning) were injected into right flanks
in each mouse. Tumors in flanks were established at day 20 and were randomized into
four groups for treatment (n>3 mice/group). We measured the tumor sizes before
treatment to ensure no clear size differences between each group (tumor size > 0.5 cm).
Mice received subcutaneous injections every other day with vehicle (a mixture of NMP,
PEG300, and 30% aqueous hydroxypropyl-β-cyclodextrin solution at 1:4:5 volume ratio,
4 ml/kg), UNI418 (10 mg/kg), Olaparib (50 mg/kg), or UNI418 + Olaparib. All mice were
sacrificed after 12 days, and tumors were removed, measured, weighed, and
photographed. The body weight of all mice was not significantly different. All animal
procedures were approved and performed according to the guidelines provided by the
Ulsan National Institute of Science and Technology’s Institutional Animal Care and Use
Committee.

Statistical analysis
Each statistical analysis for different e xperiments is described in each Figure legend.
Statistical analysis was performed by two-way ANOVA, one-way ANOVA or t-test using
GraphPad Prism software. Data are presented as means ± SEM of duplicate or triplicate
samples and significance wTas set at *P = 0.05, **P = 0.01, and ***P = 0.001.

Data Availability
All data supporting the findings of this study are available within the paper and its
Supplementary Information files. Any additional information is available from the
corresponding authors upon request. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The authors characterized a compound UNI418 that inhibits lipid kinases PIKfyve and PIP5K1C and reduces intracellular level of IP6. They showed that IP6 reduces the level of Cul4A neddylation, a scaffold protein in the CRL4 ubiquitin ligase complex, and that it leads to reduced degradation of DDR factors RAD51 and CHK1 degradation. They characterized an impact of UNI418 treatment on cell survival PARPi-resistant cells and potential implication for new therapeutic approaches This study describe a new molecular mechanism of the control of the homeostasis of central DDR factors RAD51 and CHK1. It relies on an impressive ensemble of results. Most of them are well presented and highly convincing. However, many should be strengthened before publication to ensure that the messages of the manuscript are correct (see below) There are references for previous articles on ML367 and UNI418 (for UNI418 doi: 10.1038/s12276-024-01283-2 and ref 19- 21 in the article for ML367). The authors wrote “Through high-throughput screening for compounds that modulate the DNA replication stress response, we identified ML367 and its derivative, UNI418.” The present study is not really a screening but an evaluation of the effect of previously studied compounds on another context. They indicate “Subsequent screening of approximately 100 structurally analogous derivatives of ML367 yielded compounds with enhanced efficacy in mitigating DNA replication stress.” and that “UNI418 was identified as the most effective agent” So it is an impressive piece of work, it cannot be considered as a high-throughput screening reserved to 1000 to 100 000 compounds screening. It is closer to structure-activity relationship (SAR) around the initial ML367 and UNI418 compounds. Effect of ~100 products tested The authors should present at a given concentration, the Luciferase-ATDA5 expression level for the ~100 products tested with error bars. This is an important missing information. Fig1c The error bars for the measurements with no 5-FUrd is missing In Fig1d we cannot see the effect of ML367 on RPA32 phosphorylation at 0.5µM. The authors may present the same figures with both inhibitors at 2.5µM where ML367 has an effect Ext Data Fig1d. Interestingly, UNI418 treatment reduced the level of CHK1 as well as its phosphorylation, even in the absence of DNA replication stress” It is not obvious that in presence of UNI418 and in absence of 5-FUrd. The level of Chk1 is reduced but not its phosphorylated form. Ext Data Fig1d: The experiment in presence of ML367 is not reported CHK1 expression level in presence of UNI418 “Interestingly, UNI418 treatment reduced the level of CHK1 as well as its phosphorylation, even in the absence of DNA replication stress, suggesting it affects CHK1 expression.” The authors may comment why they have not analysed the CHK1 mRNA level to further assert this statement. PIP5KIC samples. The calculated dissociation constant (KD) of PIKfyve and PIP5K1C was 0.78 nM, and 61 nM, respectively. The reviewer did not find the protocol used to express and purify PIP5KIC or provider’s name. Quality of protein samples used. The authors should put in ED a SDS-PAGE of the purified proteins Legend Fig2 KD (nM) values of PIKfyve and PIP5K1C inhibition were determined using the SelectScreen kinase assay. The authors should briefly explain in the M&M or in ED the principle of this assay. There is no Y axis or X-axis labels in Fig2D ! There is no error bars and the quality should be improved SPR analyses The blank-subtracted sensorgram data unequivocally demonstrated the direct interaction of UNI418 Precise what is the blank substracted? without UNI418 but on chip with or without MBP? ED Fig4 There was no interaction between UNI418 and MBP, which was fused to the kinases used in this study for purification (Extended Data Fig. 4). The signals with only MBP at 10µM are about 5RU vs 12RU for UNI418 substracted with (MBP or buffer ?). The difference is not sufficient to say “no interaction”. Rephrase. The fits are poor. Comment. The number after comma is meaningless. The experiment should be done in triplicate so that the KD errors are not the errors of one fit but of triplicate experiments CETSA assay. The CETSA assays are useful and convincing experiments. What is a made in triplicate? If so, please add in sources file PIPK roles in membrane trafficking “Lipid kinases, including PIKfyve and PIP5K1C, play crucial roles in phosphorylating inositol-containing molecules, which are integral to various cellular signaling pathways as second messengers.” The authors should mention that PIPK are also involved in membrane trafficking. It is only mentioned in the Discussion section Chemical schema of inositol species. The authors should add in the ED the schema of all inositol species mentioned in the manuscript for less specialist readers ED Fig 5C. The authors should improve the ED Fig5c so that the reader may better evaluate the reduction of IP6 ED with 3D modelling of UNI418 position. The authors should add in ED a zoom view of the superimposition of the ATP with the UNI418 from the Rosetta dock prediction with surrounding residues. Triplicate and Number of decimals for IC50 Notably, the IC50 values of UNI418 in HCT116 and HCT116 parp1-/- cells were measured at 1.569 μM and 0.412 μM, respectively (Fig. 3g). The authors should give error bars based on triplicate. Three decimals precision is surprising. Correct. Fig5a and ED Fig 9a Conversely supplementation with IP6, both in cells or extracts, counteracted the UNI418-induced Cul4A neddylation (Fig. 5a and Extended Data Fig. 9a). The authors should present the results with supplementation with IP6 in absence of UNI418 Rephrase UNI418-mediated reduction in HR frequency, attributed to the proteolysis of HR proteins by activated Cul4A ubiquitin ligase following down-regulation of IP6 via inhibition of PIKfyve/PIP5K1C by UNI418, was also restored upon additional supplementation of IP6 Rephrase ! Suggestion. “UNI418-mediated reduction in HR frequency was also restored upon additional supplementation of IP6 IP6 toxicity However, it is important to note that IP6 exhibited toxicity in both WT and parp1-/- cells. The authors may show in ED the data Partial knockdown In contrast, WDR5 knockdown did not increase CtIP levels (data not shown). The authors mention here and elsewhere “knockdown” of proteins while the levels of the proteins upon siRNA treatments are only weakened. They should precise and comment the potential impact of residual levels of the proteins Fig6d, the authors should add the level of RFWD3 in presence of siRNA Combined use of UNI418 and Oliparib Crucially, this increase in drug sensitivity was paralleled by a marked elevation in apoptotic cell death among the PARPi resistant C4-2 cells following UNI418 treatment The effect is less significative with combined use of UNI418 and Oliparib. The authors may indicate and comment Redundancy End of results part and beginning of discussion are redundant.", "reviewer_2": "In their study titled \"Targeting IP6 signaling to destabilize homologous recombination proteins to overcome PARP inhibitor resistance” the authors present their findings demonstrating that targeting lipid kinases with the novel inhibitor UNI418 leads to a reduction in inositol hexaphosphate levels, in turn causing the degradation of homologous recombination proteins and a reduction in homologous recombination efficiency. This translates to a re-sensitization to PARP inhibitor in chemoresistance triple negative breast cancer cell lines. The data presented are generally convincing and I feel elucidate an interesting potential mechanism by which homologous recombination is regulated via proteasomal degradation signalled by inositol hexaphosphate levels. I have a few suggestions and concerns that I recommend be addressed to consolidate the work, and some comments to help improve the manuscript. 1. Data transparency – To facilitate data transparency, I suggest the authors show individual data points on all graphs so that readers get a better sense of the data distribution in experiments. 2. Western blot quantification – The authors mention several times that protein levels are significantly or substantially changed between different treatment conditions, but do not consistently present quantified data of relevant immunoblots supported with statistical tests to back up these otherwise only qualitative claims. I recommend that the authors include relevant quantifications of immunoblot data (where these claims are directed) to better support any assertions. The use of superlatives to describe changes should also be limited and/or fully removed, as these have limited quantitative meaning. 3. DNA Replication Stress Response – In figure 1, the authors measure DNA replication stress response suppression by induction of ATAD5. I am wondering how inhibition by the two small molecule inhibitors compares to inhibition of CHK1 phosphorylation via ATR inhibition, as that could be a good positive control for suppression of certain facets of the DNA replication stress response. 4. DNA replication stress response inhibition – Induction of ATAD5 between ML367 and UNI418 are different in figure 1C, making it difficult to make any comparison about suppression of DNA replication stress response as currently presented in the manuscript. Another interpretation could be that both inhibitors function similarly as they both result in ~75% reduction in signal at the highest concentration of inhibitor. Furthermore, the authors do not make any comparisons between dissociation constants or IC50 between ML367 and UNI418 in the text, which would allow readers to draw conclusions whether UNI418 displays heightened suppression of the DNA replication stress response. I suggest the authors make mention of these values to support their claims. 5. RAD51 Foci quantification in Figure 3 – please describe if this was done manually or whether an automated foci detection system was used. If the latter was used, please provide a brief description of the pipeline in the methods section. a. It is also important to understand whether cells in G2 phase were distinguished from cells in S-phase (at the time of irradiation / analysis of foci), as DSB repair processes between each phase are distinct. In the context of this work, selective analysis of cells irradiated in S-phase and analyzed in S-phase would be most logical. b. The legends indicate that these cells were monitored 1 hour after 10 Gy, a dose and time point that I am honestly very surprised that “only” an average of ~15 RAD51 foci are observed in the control / DMSO. From experience and understanding of comparable literature, foci numbers at least twice this are anticipated, as 10 Gy would be predicted to induce 100-200 DNA breaks in a G1 phase cell and 200-400 breaks in a G2 phase cell (with intermediate numbers in S-phase) depending on cell type genome content. While not all IR-induced breaks will undergo HR and form RAD51, at least 1/3 of induced breaks at any given time are expected to. It is not uncommon for radiation dosimetry here to vary substantially between groups if irradiator calibration is not up-to-date, or it could be possible that too many breaks are occurring and challenging for the authors to separate (foci are merging). I would advise the authors to examine this issue more closely in the context of what is understood from the published literature, as these numbers do appear far less than expected for that dose. c. Finally, while Figure 3B is helpful, it is a single time point and understanding whether the UNI418 specific effect is transient by performing a few timepoints in addition to the 1h would be helpful. 6. DSB Repair Efficiency – In figure 3F, the authors show both a large reduction in HR efficiency and a small reduction in NHEJ efficiency when cells are treated with UNI418 in the I-Sce1 plasmid reporter assay. Testing whether the repair of genomic breaks by monitoring foci numbers in G1, S, and G2 cells over a time course following some other form of genotoxic stress would further support the claims of reduced repair efficiency and validate the observations with the plasmid-based assay, which are otherwise not able to distinguish effects between phases. HU, IR, ATR inhibitors, Camptothecin, or even endogenous DNA replication stress might be used in this context – with the most important thing being to monitor damage formed and resolved in S-phase separately from other phases. 7. Synthetic lethality with Olaparib – it would be interesting to see how cell survival in the combination treatment compares to cell survival when BRCA1 or BRCA2 are knocked down by siRNA, as this is the canonical example of synthetic lethality in DNA repair. 8. PARPi resistance and re-sensitization – In Figure 7, the authors examine PARPi resistance by BRCA2 reversion, but there are quite a few known and different mechanisms that cells (especially cancer cells) can leverage to become more resistant to PARPi action. It would be interesting to see whether BRCA1/2 negative cells that have restored homologous recombination repair due to TP53BP1 loss, or resistance due to increased efflux pump expression, are re-sensitized to PARPi when treated with UNI418. 9. Big Picture – It is not clear within the discussion whether the authors think that their tool compounds can be modified for therapeutic purposes, and this would be helpful. I was also expecting some discussion about differences in IP6 and related biosynthetic processes between normal and cancer cells, and between different cancer types that naturally would have plenty of metabolic variation given their context and specific genomic profile. Minor Comments: 10. “DNA repair” – throughout this manuscript, the words “DNA repair” are used to actually refer to “DNA double strand break repair” or similar. The processes being discussed here are specific to that type of DNA damage in the context of DNA replication, and not all possible types of DNA damage that exist. Please amend all instances of that language to be specific. 11. Western blot loading control –In figure 1b, the appropriate loading control for pRPA32 is total RPA32 levels, please include this control. H3 is less ideal in the context of that experiment. 12. How these inhibitors are referred to – generally it is advisable to be specific and call them PARP1/2-trapping inhibitors, as other small molecules that block PARP enzyme action exist, with no to variable impact on trapping PARP enzymes at sites of DNA leading to damage. 13. Data normalization –In Figure 1A, it is not clearly stated whether the Luc-ATAD5 data is normalized or not. The authors should revise all figures and clearly state whether the data is normalized, and if so, what the data is normalized to. 14. Phosphorylation of CHK1 – I would suggest including the blot of phospho-CHK1 in the main body of the manuscript in figure 1. 15. Kinase screen – I suggest the authors include extended data figure 2 in the main body as it guides the narrative of the study. I would also ask for more details on what precent control is referring to, and that the authors label the kinases of interest within the plot to make it more clear to the reader. 16. Figure 2A is missing axis labels, please include these. 17. Surface plasmon resonance – In figure 2B, there is no description of what the black lines underneath the coloured lines represent. Please describe what these are or remove them. 18. The methods section describes two cell viability assays, but it is not clear in the figure which one is used for each dataset. Please include this information within the appropriate figure legends. It is also not clear why two different cell viability assays need to be used. 19. Representative images of clonogenic cell survival assays – When appropriate, I would appreciate the if the authors included representative images of their cell survival assays, specifically clonogenic cell survival assays. 20. CUL4A neddylation – Figure 5A and 5B are missing a control that clearly demonstrates that the higher molecular weight CUL4A band is clearly CUL4A-Nedd. The authors should include a blot demonstrating that this band does not appear in the presence of an inhibitor of neddylation such as the compound MLN4924 used in reference 39. 21. I would recommend the authors merge the graphs in extended data 9C and used dash lines to represent additional treatments. 22. IPPK siRNA – The authors did not include a control demonstrating the effectiveness of their siRNA against IPPK. 23. In figure 6C, the authors make the claim that silencing WDR or CUL4A causes resistance to Olaparib, but only show comparison compared to vehicle controls. To support this claim, please show the results of the statistical test between the different siRNAs at 20 µM and 40 µM Olaparib.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "This manuscript by Dr. Myung’s group reports the identification and characterization of UNI418, a derivative of ML367, as an inhibitor of PIKfyve and PIP5K1C. The authors demonstrate that UNI418 inhibits the phosphatidyl inositol pathway, thereby activating the Cul4A–DDB1–WDR5 E3 ligase complex, which targets RAD51 and CHK1 for proteolysis. Consequently, UNI418 impairs HR, sensitizes tumor cells to PARP inhibitors, and overcomes PARPi resistance. I find this study both interesting and novel. The data are extensive and address the problem from multiple perspectives, making the manuscript potentially suitable for Nature Communications. I do not fundamentally disagree with the authors’ conclusions; however, I have several concerns regarding the interpretation and presentation of the results, as detailed below. I believe these points should be addressed to strengthen the manuscript. Introduction • The introduction should include the background of ATAD5. The authors state that ML367 was identified in 2010 and shown to increase ATAD5 protein levels under replication stress. Since UNI418 is a derivative of ML367, these facts, as well as the functional relevance of ATAD5 stabilization, should be included. Is it generally accepted that ATAD5 stabilization reflects replication stress? Figure 1 • The authors used 5-FU for 16–24 hours to induce replication stress. However, 5-FU is not a standard agent for inducing replication stress in cancer cells, and indeed pRPA32 was only modestly increased (Fig. 1d). Would similar results be obtained with other established replication stress inducers such as HU or camptothecin? • In Fig. 1d and e, the blot for total RPA2 should be shown. The CHK1 blot from Extended Data Fig. 1b could be moved to the main figure because it is the key point of Figure 1. • I recommend including supplementary data using alternative replication stress–inducing drugs to validate the conclusion that UNI418 represses replication stress. Figure 2 • Fig. 2a: The x-axis should be annotated. • Fig. 2d: The phosphatidylinositol pathway may be unfamiliar to many readers primarily interested in DNA damage responses and PARPi. A schematic explaining the relationships among PIKfyve, PI(3)P, PI(3,5)P2, and related molecules would be helpful. Figure 3 • Fig. 3a: The authors report that RAD51, CHK1, and CtIP are downregulated upon UNI418 treatment. However, RAD51 remains at a detectable level. o I strongly recommend performing a quantitative proteomic analysis to determine how many proteins are affected by UNI418. Is RAD51 one of a few or one of many targets? o The reduction in RAD51 should also be quantified from immunoblots and immunofluorescence (total levels, not just foci, if measurable). o Please also consider the literature: heterozygosity of key HR genes (RAD51, BRCA1/2) often does not produce strong phenotypes. For example, comparisons to RAD51+/- versus -/- (or BRCA1+/- vs. BRCA1-/-) cells can be found elsewhere. • Fig. 3b: A statistical analysis of UNI418 alone versus UNI418 + IR is warranted, as the remaining RAD51 foci formation appears different from the general BRCA1/2-deficient phenotype (no RAD51 foci formed). • Fig. 3c could be moved to Extended Data. • Fig. 3f: The reduction in HR frequency with UNI418 is much milder than with siRAD51. Please provide immunoblots of RAD51 under UNI418 and siRAD51 for comparison. • Fig. 3g: “parp1-/-” should be capitalized as “PARP1-/-” since it refers to the human gene knockout. • Fig. 3g and 3i: The authors used 0.25 μM UNI418, described as non-toxic to both cell types. If UNI418 is a catalytic inhibitor, why does its toxicity display clear dose dependence in PARP1-/- cells? Does RAD51 protein level also show dose-dependency by UNI418? o I am concerned that the apparent hypersensitivity of PARP1-/- cells by a dose-dependent UNI418 (1-5 uM >>0.25 uM) could reflect off-target effects, such as induction of PARP1-dependent DNA damage (base damage?). o Please include dose–response experiments (0, 0.25, 0.5, 1, 2.5, 5 μM) to clarify this issue. Figure 4 • Fig. 4a: Since CHK1 is markedly reduced, its role in the drug sensitivity data must be considered. CHK1 inhibition is known to synergize with PARPi because PARPi-induced replication stress activates the ATR–CHK1 pathway. The authors should evaluate whether CHK1 suppression contributes to the observed olaparib sensitivity. • Fig. 4d: The sensitivity observed is mild (y-axis begins at 60%). HR-deficient cells are typically hypersensitive to olaparib at low micromolar or even nanomolar concentrations. o Please add control data for siBRCA1, siBRCA2, or siRAD51 cells for comparison. o The addition of UNI418 in these knockdown experiments (e.g., siPIKfyve + UNI418) would be informative. Figure 5 • Fig. 5a–b: The quantification is problematic. The Actin loading control is uneven, and the differences are marginal. Consider removing these panels if your conclusions remain supported without them. • Please illustrate a pathway for how excess IP6 diminishes Cul4A neddylation. • Fig. 5b: There is no additive effect of PIP5K1C knockdown and PIKfyve knockout, which appears inconsistent with Fig. 4d. Please discuss. • Fig. 5c: RAD51, CHK1, and CtIP levels increase under siCUL4A, but also under UNI418 treatment. The authors should provide an unbiased interpretation. Figure 6 • Fig. 6c: In siCtl cells, olaparib induces 20–40% cell death at 20–40 μM. Since the MOA of olaparib in HR-proficient cells is PARP trapping, these results need further explanation. How can siCUL4A or related treatments “rescue” HR-proficient cells? Excess RAD51 alone is unlikely to confer “super-HR” proficiency. Please consider alternative interpretations. Figure 7 • Fig. 7d, e, g, h: C4-2 and C2-2 cells (HR-proficient due to BRCA reversion mutations) are unexpectedly more sensitive to treatment. Please clarify why. • As the authors noted in the Introduction, the synthetic lethality between PARP deficiency and BRCA1/2 deficiency is commonly explained by ssDNA gap accumulation, fork reversal, and transcription–replication collisions. To reproduce these effects, genuine HR deficiency together with PARP catalytic inhibition is required. Importantly, PARP catalytic inhibition is fully achieved at concentrations below 1 μM olaparib. However, the data shown in Figure 7 demonstrate a dose-dependent effect of olaparib in the range of 1–10 μM, which is unlikely to reflect catalytic inhibition but rather PARP trapping. This makes the apparent effectiveness of the UNI418 and PARP-/- combination difficult to interpret. Given that the precise mechanism of action of PARP inhibitors, particularly in BRCA-deficient backgrounds, remains controversial, the authors should avoid attributing their findings solely to PARP inhibition. Additional testing with DNA-damaging agents such as camptothecin or cisplatin would help to substantiate whether the observed effects indeed arise from HR defects."}, "author_response": "Dear Editor and Reviewers, We would like to thank the reviewers for their constructive and insightful comments. We have carefully revised the manuscript in response to all points raised. Below, we provide a detailed, point-by-point response, and all changes have been incorporated into the revised manuscript. We believe these revisions have significantly improved the clarity and impact of our work. Reviewer #1 Comment 1: Fig1c The error bars for the measurements with no 5-FUrd are missing Response: The error bars for the “no 5-FUrd” condition are included; however, the variation in these measurements is extremely small, and therefore the error bars are not visually discernible at the current graph scale. To ensure transparency, we have provided the exact numerical values for each data point in the Source Data file. Comment 2: In Fig1d we cannot see the effect of ML367 on RPA32 phosphorylation at 0.5µM. The authors may present the same figures with both inhibitors at 2.5µM where ML367 has an effect. Ext Data Fig1d. Interestingly, UNI418 treatment reduced the level of CHK1 as well as its phosphorylation, even in the absence of DNA replication stress” It is not obvious that in presence of UNI418 and in absence of 5-FUrd. The level of Chk1 is reduced but not its phosphorylated form. Ext Data Fig1d: The experiment in presence of ML367 is not reported. CHK1 expression level in presence of UNI418 “Interestingly, UNI418 treatment reduced the level of CHK1 as well as its phosphorylation, even in the absence of DNA replication stress, suggesting it affects CHK1 expression.” The authors may comment on why they have not analyzed the CHK1 mRNA level to further assert this statement. Response: As several reviewers raised similar concerns, we performed additional experiments to clarify the effects of UNI418 and ML367 on CHK1 and phosphor-CHK1 levels. For these new experiments, we adjusted the concentration of ML367 to 10 µM, at which its effects were more clearly detectable than at 0.5 µM. Our new data show that, even in the absence of 5-FUrd, UNI418 reduces both p-CHK1 and total CHK1 levels more robustly than ML367. We also observed the same trend under 5-FUrd treatment, indicating that UNI418 consistently suppresses CHK1 signaling regardless of replication stress conditions (now Extended Data Fig. 1b). Furthermore, as presented in Extended Data Fig. 6e, UNI418 does not alter CHK1 mRNA levels under replication-stress-free conditions, suggesting that the reduction in CHK1 protein is not driven by transcriptional downregulation. We have updated the figures and the corresponding text to reflect these new findings. Comment 3: PIP5KIC samples. The calculated dissociation constant (KD) of PIKfyve and PIP5K1C was 0.78 nM, and 61 nM, respectively. The reviewer did not find the protocol used to express and purify PIP5KIC or provider’s name. Response: Thanks for the comment. We have now added the relevant details to the Methods section of the manuscript. Specifically, we have included the following description: “The gene encoding the kinase domain of human PIKfyve and PIP5K1C was amplified from GFP-hPIKfyve and GFP-PIPK1 gamma 90 (GFP-PIP5K1C) plasmids purchased from Addgene (#121148 and #22299), and cloned into the expression vector pVFT4S, which contains a poly-histidine tag, a maltose-binding protein (MBP), and a tobacco etch virus (TEV) protease recognition site.” This added information clarifies the source of the constructs and the cloning strategy used for protein expression and purification. Comment 4: Quality of protein samples used. The authors should put in ED an SDS-PAGE of the purified proteins Response: Thanks for the comment. To address the concern regarding the quality of the purified proteins samples, we have now included an SDS-PAGE gel image in Extended Data Fig. 3a, which shows the purity of the proteins used in this study. Comment 5: Fig2 KD (nM) values of PIKfyve and PIP5K1C inhibition were determined using the SelectScreen kinase assay. The authors should briefly explain in the M&M or in ED the principle of this assay. There are no Y axis or X-axis labels in Fig2D! There are no error bars, and the quality should be improved. Response: We have added a brief explanation of the SelectScreen® kinase assay to the Methods section of the revised manuscript, describing the assay principle and workflow used to determine KD values for PIKfyve and PIP5K1C. Specifically, the following description has been included in the Methods section: “Kinase assays were performed using the SelectScreen® Kinase Profiling platform (Thermo Fisher Scientific). Kinase-tagged T7 phages were produced in an E. coli BL21- derived host, and additional kinases were expressed in HEK293 cells and subsequently DNA-tagged for qPCR detection. Streptavidin-coated magnetic beads were incubated with biotinylated small-molecule ligands to generate affinity resins, followed by blocking with buffer to minimize nonspecific binding. Binding reactions were assembled by mixing kinases, ligand-coupled beads, and test compounds in binding buffer (20% SeaBlock, 0.17× PBS, 0.05% Tween-20, 6 mM DTT). Test compounds were applied as an 11-point 3-fold serial dilution series, with a final DMSO concentration of 0.9%. Reactions were carried out in 384-well plates at a final volume of 20 µL and incubated for 1 h at room temperature. Beads were then washed and resuspended in elution buffer containing 0.5 µM non-biotinylated ligand. The concentration of eluted kinases was quantified by qPCR, and dissociation constants (KD) were determined from concentration–response curves.” Sorry not to provide better graph in the original submission. We have improved the quality of Fig 2d (now Fig. 2b) by replacing the original graph which was provided by the company with a newly generated version using GraphPad Prism with actual dataset, which now includes clear X- and Y-axis labels, error ranges and higher graphical clarity. Comment 6: SPR analyses the blank-subtracted sensorgram data unequivocally demonstrated the direct interaction of UNI418 Precise what is the blank substracted? without UNI418 but on chip with or without MBP? ED Fig4 There was no interaction between UNI418 and MBP, which was fused to the kinases used in this study for purification (Extended Data Fig. 4). The signals with only MBP at 10µM are about 5RU vs 12RU for UNI418 substracted with (MBP or buffer?). The difference is not sufficient to say, “no interaction”. Rephrase. The fits are poor. Comment. The number after comma is meaningless. The experiment should be done in triplicate so that the KD errors are not the errors of one fit but of triplicate experiments Response: In our SPR experiments, the term “blank” refers to the signal obtained when the chip is immobilized with MBP–PIKfyve or MBP–PIP5K1C and an injection containing only DMSO— at the same concentration used to solubilize UNI418—is flowed over the surface. This subtraction step removes refractive-index changes and bulk shifts originating from DMSO, ensuring that the sensorgrams reflect only the binding response induced by UNI418 itself. This clarification has been added to the revised manuscript. “UNI418 was then injected as an analyte over the chip surface, and changes in resonance units (RU), which reflect molecular mass accumulation on the sensor surface, were monitored. Sensorgrams were generated to visualize the interaction kinetics. To ensure accurate measurement of compound-specific binding, sensorgrams were blank- subtracted using signals obtained from injections containing DMSO alone at the same concentration used to solubilize UNI418.” In Extended Data Fig. 4 (now Extended Data Fig 3b), we immobilized purified MBP alone on the chip and injected UNI418 at 1, 2, 5, and 10 µM. Although MBP produced a small RU response, the signal decreased over time, indicating that the interaction is transient and unlikely to represent a specific binding event. These data were included to demonstrate that the responses observed when MBP–PIKfyve or MBP–PIP5K1C were immobilized are not attributable to nonspecific interaction with the MBP tag but instead arise from specific interaction with the respective kinase domains. Regarding the fitting quality, UNI418 requires DMSO for solubility. The experiment was performed using the highest DMSO concentration recommended for Biacore instruments, which inevitably limits curve-fitting quality. While slight deviations are observed at higher analyte concentrations, the predicted fit curves follow the experimental data reasonably well across the full concentration range. Importantly, we performed the experiment in three independent replicates, and the calculated KD values were highly consistent across repeats, supporting the robustness of the measurements. The replicate sensorgrams and KD calculations are provided in the Source Data file, and the KD values reported in the revised manuscript now include error estimates derived from these triplicate experiments. Comment 7: CETSA assay. The CETSA assays are useful and convincing experiments. What is a made in triplicate? If so, please add in sources file. Response: We confirm that the CETSA assays were performed in three independent biological replicates. The full raw data from all three replicates are included in the Source Data file, as requested. Comment 8: PIPK roles in membrane trafficking “Lipid kinases, including PIKfyve and PIP5K1C, play crucial roles in phosphorylating inositol-containing molecules, which are integral to various cellular signaling pathways as second messengers.” The authors should mention that PIPK are also involved in membrane trafficking. It is only mentioned in the Discussion section. Response: The sentence “Lipid kinases, including PIKfyve and PIP5K1C, play crucial roles in phosphorylating inositol-containing molecules, which are integral to various cellular signaling pathways as second messengers.” appears in the Results section of the original manuscript and introduces the enzymatic and signaling characteristics of these kinases. In addition, we agree with the reviewer that PIKfyve and PIP5K1C also play important roles in membrane trafficking. To address this point, we have further emphasized their trafficking-related functions in the Discussion section. Specifically, we added the following text: “The tumor regression induced by UNI418 may rely not only on HR protein degradation but also on pleiotropic effects associated with PIKfyve and PIP5K1C inhibition. These lipid kinases regulate the generation of PI(3,5)P and PI(4,5)P , which are essential for 2 2 endosomal and lysosomal membrane dynamics as well as autophagy activation. Therefore, UNI418-mediated disruption of cellular homeostasis may contribute to the observed antitumor response.” Comment 9: Chemical schema of inositol species. The authors should add in the ED the scheme of all inositol species mentioned in the manuscript for less specialist readers. Response: Thanks for the suggestion. We have added a schematic representation of all inositol species mentioned in the manuscript to Fig. 2e, so that readers who are less familiar with inositol metabolism can more easily follow the content. This addition has been incorporated into the revised manuscript. Comment 10: ED Fig 5C. The authors should improve the ED Fig5c so that the reader may better evaluate the reduction of IP6. Response: To more clearly demonstrate the reduction of IP6 levels upon UNI418 treatment, we performed the experiment again with three independent replicates. The data were re- plotted using Prism to improve clarity and readability, and the updated graph has been incorporated into now Extended Data Fig. 4c in the revised manuscript. Comment 11: ED with 3D modelling of UNI418 position. The authors should add in ED a zoom view of the superimposition of the ATP with UNI418 from the Rosetta dock prediction with surrounding residues. Response: Following the recommendation, we have added a zoomed-in view showing the superimposition of ATP and UNI418 from the Rosetta docking prediction, along with the surrounding residues. This detailed structural comparison has been included in now Extended Data Fig. 5a of the revised manuscript. Comment 12: Triplicate and Number of decimals for IC Notably, the IC50 values of UNI418 in HCT116 50 and HCT116 parp1-/- cells were measured at 1.569 µM and 0.412 µM, respectively (Fig. 3g). The authors should give error bars based on triplicate. Three decimals precision is surprising. Correct. Response: Based on the raw data, we recalculated the IC values and now report them to two 50 decimal places instead of three. In addition, we performed the analysis using three independent biological replicates, and the corresponding error ranges (±) have been included in the revised figure. These updates are reflected in the revised version of Fig. 3f and the Source Data file. Comment 13: Fig5a and ED Fig 9a Conversely supplementation with IP , both in cells or extracts, 6 counteracted the UNI418-induced Cul4A neddylation (Fig. 5a and Extended Data Fig. 9a). The authors should present the results with supplementation with IP in absence of 6 UNI418 Response: As recommended, we recognized that the group treated with IP alone had not been 6 included in the original experiment. We therefore performed an additional set of experiments in which cells or extracts were treated with IP in the absence of UNI418, 6 with three independent biological replicates. The newly generated data (Fig. 5a and Extended data Fig. 9a) have been added to the revised figures and included in the Source Data file. Comment 14: Rephrase UNI418-mediated reduction in HR frequency, attributed to the proteolysis of HR proteins by activated Cul4A ubiquitin ligase following down-regulation of IP via 6 inhibition of PIKfyve/PIP5K1C by UNI418, was also restored upon additional supplementation of IP Rephrase! Suggestion. “UNI418-mediated reduction in HR 6 frequency was also restored upon additional supplementation of IP . 6 Response: As recommended, we have revised the sentence to the clearer phrasing: “UNI418-mediated reduction in HR frequency was also restored upon additional supplementation of IP .” This change has been incorporated into the revised manuscript. 6 Comment 15: IP6 toxicity However, it is important to note that IP exhibited toxicity in both WT and 6 parp1-/- cells. The authors may show in ED the data. Response: In our study, IP supplementation was performed as a brief 10-minute treatment. The 6 goal of IP6 supplementation in our assays was to transiently restore intracellular IP 6 levels rather than to maintain long-term IP elevation, which is typically associated with 6 cytotoxic effects. For this reason, cytotoxicity was not expected in our experimental setup. We have added a clarifying statement in the revised manuscript to explain why toxicity was not assessed in this context. Comment 16: Partial knockdown In contrast, WDR5 knockdown did not increase CtIP levels (data not shown). The authors mention here and elsewhere “knockdown” of proteins while the levels of the proteins upon siRNA treatments are only weakened. They should precise and comment the potential impact of residual levels of the proteins. Response: As described in the manuscript, our screening strategy was designed to identify the DCAF responsible for RAD51 proteolysis. Based on the established role of DCAFs in determining Cul4A substrate specificity, we screened more than 60 predicted DCAFs using siRNAs and monitored RAD51 and CHK1 levels. WDR5 was the only candidate whose silencing consistently increased both proteins, and we therefore focused our analysis on WDR5 as the relevant DCAF. WDR5 was identified through screening with RAD51 and CHK1 as readouts. However, WDR5 knockdown shows minimal or no effect on CtIP, which is likely regulated by a different DCAF or degradation pathway. We commented it in the revised manuscript. Furthermore, to assess whether residual protein levels from partial knockdown may influence the results, we performed experiments under MG132 treatment, which fully blocks proteolysis. Under these conditions, the effects of WDR5 and CUL4A knockdown were further enhanced, supporting the conclusion that the observed phenotypes were indeed limited by the presence of residual protein. We commented it in the revised manuscript. “In contrast, WDR5 knockdown did not increase CtIP levels (data not shown), which suggest CtIP is regulated by other DCAF. Additional proteasome inhibition using MG132 showed further enhancement of the observed effects, suggesting that residual protein levels due to incomplete knockdown of WDR5 and CUL4A may have masked the full recovery of RAD51 and CHK1 (data not shown).” This figure is not included in the revised manuscript. It is only for reviewers. Comment 17: Fig. 6d, the authors should add the level of RFWD3 in presence of siRNA. Response: To examine RFWD3 levels upon siRNA treatment, we purchased the commercially available antibody cited in previously published studies and performed immunoblotting. However, the antibody did not yield a detectable or specific signal under our experimental conditions, making it difficult to reliably assess RFWD3 protein levels. As an alternative, we measured RFWD3 mRNA expression by qPCR, and these results were added to Extended Data Fig. 9g in the revised manuscript. Comment 18: Combined use of UNI418 and Oliparib Crucially, this increase in drug sensitivity was paralleled by a marked elevation in apoptotic cell death among the PARPi resistant C4-2 cells following UNI418 treatment The effect is less significative with combined use of UNI418 and Oliparib. The authors may indicate and comment. Response: We thank the reviewer for pointing out this issue. Upon careful re-examination of the data used in the original submission, we identified an error in the dataset associated with the apoptotic cell death analysis in the combination treatment condition. This error affected the apparent magnitude of the effect observed with the combined use of UNI418 and Olaparib. We have now corrected the dataset, re-plotted the graphs, and re-performed the statistical analyses using the corrected values. Following this correction, the revised data accurately reflect the effects of UNI418 alone and in combination with Olaparib in PARPi- resistant C4-2 cells. The updated figures and statistical analyses have been incorporated into the revised manuscript (Fig. 7i). We apologize for any confusion caused by the initial error and appreciate the reviewer’s careful assessment, which helped us improve the accuracy and clarity of the presented data. Comment 19: Redundancy End of results part and beginning of discussion are redundant. Response: We agree that the opening statement of the Discussion section partially overlapped with the concluding paragraph of the Results. To address this redundancy, we have removed the overlapping explanatory sentences from the beginning of the Discussion and reorganized the opening paragraph to ensure that the Discussion section no longer repeats information presented in the Results. Reviewer #2 Comment 1: Data transparency – To facilitate data transparency, I suggest the authors show individual data points on all graphs so that readers get a better sense of the data distribution in experiments. Response: In accordance with the recommendation, we have revised all graphs throughout the manuscript to display individual data points. These updated figures are included in the revised manuscript. Comment 2: Western blot quantification – The authors mention several times that protein levels are significantly or substantially changed between different treatment conditions, but do not consistently present quantified data of relevant immunoblots supported with statistical tests to back up these otherwise only qualitative claims. I recommend that the authors include relevant quantifications of immunoblot data (where these claims are directed) to better support any assertions. The use of superlatives to describe changes should also be limited and/or fully removed, as these have limited quantitative meaning. Response: To address this concern, we have now included quantitative analyses for the key immunoblot data supporting our conclusions. For the relevant experiments, three independent biological replicates were performed, and representative full immunoblot images from all repeats have been provided in the Source Data files. Band intensities were quantified using ImageJ, and values were normalized to the appropriate loading controls (α-tubulin, GAPDH, or histone H3, as indicated for each experiment). The normalized values are now displayed numerically above each corresponding band in the figures. Comment 3: DNA Replication Stress Response – In figure 1, the authors measure DNA replication stress response suppression by induction of ATAD5. I am wondering how inhibition by the two small molecule inhibitors compares to inhibition of CHK1 phosphorylation via ATR inhibition, as that could be a good positive control for suppression of certain facets of the DNA replication stress response. Response: To address this point, we incorporated ATR inhibitor (ATRi) as a positive control for suppression of the DNA replication stress response. In the revised figure, we now directly compare each treatment condition individually—ML367, UNI418, and ATRi—by examining their respective effects on p-CHK1 and total CHK1 levels. Comment 4: DNA replication stress response inhibition – Induction of ATAD5 between ML367 and UNI418 are different in figure 1C, making it difficult to make any comparison about suppression of DNA replication stress response as currently presented in the manuscript. Another interpretation could be that both inhibitors function similarly as they both result in ~75% reduction in signals at the highest concentration of inhibitors. Furthermore, the authors do not make any comparisons between dissociation constants or IC between 50 ML367 and UNI418 in the text, which would allow readers to draw conclusions about whether UNI418 displays heightened suppression of the DNA replication stress response. I suggest the authors make mention of these values to support their claims. Response: Thanks for the comment. To clarify the relative effects of ML367 and UNI418 on the DNA replication stress response, we examined the quantitative values provided in the Source Data for ATAD5 luciferase activity. At the highest concentration tested (5 µM), ML367 reduced ATAD5 luciferase activity by approximately 70% compared to the 5-FUrd–treated control, whereas UNI418 reduced the signal by approximately 90% under the same conditions. These measurements indicate a substantially stronger suppression of replication stress signaling by UNI418 relative to ML367. To facilitate interpretation of these differences, we have updated Fig. 1c to report the IC values for ATAD5 luciferase activity, which further substantiates the conclusion that 50 UNI418 more potently suppresses the replication stress response. Comment 5: RAD51 Foci quantification in Figure 3 – please describe if this was done manually or whether an automated foci detection system was used. If the latter was used, please provide a brief description of the pipeline in the methods section. a. It is also important to understand whether cells in G2 phase were distinguished from cells in S-phase (at the time of irradiation / analysis of foci), as DSB repair processes between each phase are distinct. In the context of this work, selective analysis of cells irradiated in S-phase and analyzed in S-phase would be most logical. b. The legends indicate that these cells were monitored 1 hour after 10 Gy, a dose and time point that I am honestly very surprised that “only” an average of ~15 RAD51 foci are observed in the control / DMSO. From experience and understanding of comparable literature, foci numbers at least twice this are anticipated, as 10 Gy would be predicted to induce 100-200 DNA breaks in a G1 phase cell and 200-400 breaks in a G2 phase cell (with intermediate numbers in S-phase) depending on cell type genome content. While not all IR-induced breaks will undergo HR and form RAD51, at least 1/3 of induced breaks at any given time are expected to. It is not uncommon for radiation dosimetry here to vary substantially between groups if irradiator calibration is not up-to-date, or it could be possible that too many breaks are occurring and challenging for the authors to separate (foci are merging). I would advise the authors to examine this issue more closely in the context of what is understood from the published literature, as these numbers do appear far less than expected for that dose. c. Finally, while Figure 3b is helpful, it is a single time point and understanding whether the UNI418 specific effect is transient by performing a few timepoints in addition to the 1h would be helpful. Response: Thanks for the comment. RAD51 foci were quantified using confocal microscopy followed by semi-automated analysis in ZEN software (Carl Zeiss). Images were acquired on an LSM880 confocal microscope using identical acquisition settings for all samples. After background subtraction, nuclei were segmented based on DAPI, and RAD51 foci were quantified exclusively in EdU-positive nuclei, which had been identified following Click-iT detection. Foci were detected using the ZEN spot detection module with fixed thresholding parameters applied uniformly across all samples. Quantification was performed on ≥50 EdU-positive nuclei per condition. These details have been added to the Methods section. To address reviewer’s comment, we redid experiments several times more after recalibrating our x-ray machine. a. To address concerns regarding cell-cycle heterogeneity, we restricted our analysis to S-phase cells identified by EdU incorporation. Cells were pulse-labeled with EdU after irradiation, followed by Click-iT detection immediately prior to imaging. Only EdU-positive nuclei were included in the RAD51 foci quantification. This clarification has been added to Fig. 3b. b. b. In our repeated experiments, S-phase cells exhibited an average of more than 30 RAD51 foci at the 1 h time point. Reported values in the literature vary substantially depending on cell type, irradiation conditions, and quantification methods, ranging widely from ~20 to >80 foci. Therefore, the values observed in our experiments fall within the variability reported across published studies. c. In response to the reviewer’s suggestion, we examined RAD51 foci at 1 h, 3 h, and 6 h after irradiation. The suppressive effect of UNI418 on RAD51 foci was observed at all timepoints, indicating that the effect is not transient. Comment 6: DSB Repair Efficiency – In figure 3F, the authors show both a large reduction in HR efficiency and a small reduction in NHEJ efficiency when cells are treated with UNI418 in the I-Sce1 plasmid reporter assay. Testing whether the repair of genomic breaks by monitoring foci numbers in G1, S, and G2 cells over a time course following some other form of genotoxic stress would further support the claims of reduced repair efficiency and validate the observations with the plasmid-based assay, which are otherwise not able to distinguish effects between phases. HU, IR, ATR inhibitors, Camptothecin, or even endogenous DNA replication stress might be used in this context – with the most important thing being to monitor damage formed and resolved in S-phase separately from other phases. Response: We appreciate the reviewer’s thoughtful suggestion. We fully agree that monitoring DSB repair kinetics in G1, S, and G2 cells following genotoxic stress would provide additional mechanistic insight. However, performing a full cell-cycle–resolved time-course analysis using multiple markers (γH2AX, 53BP1, RAD51) is beyond the scope and technical feasibility of the current revision timeline. Importantly, our study already incorporates several complementary assays that directly assess HR repair efficiency in S-phase cells: • EdU-based RAD51 foci quantification (Fig. 3b), • I-SceI DR-GFP reporter assay (Fig. 3e), • Effects of UNI418 on replication-stress–induced DDR signaling (Fig. 1), all of which consistently demonstrate that UNI418 markedly reduces HR activity. While we agree that additional time-course experiments could provide further detail, the combined results from our existing assays robustly support the conclusion that UNI418 impairs HR-mediated DSB repair. Comment 7: Synthetic lethality with Olaparib – it would be interesting to see how cell survival in the combination treatment compares to cell survival when BRCA1 or BRCA2 are knocked down by siRNA, as this is the canonical example of synthetic lethality in DNA repair. Response: To address this point, we performed additional experiments using siBRCA2 as HR- deficient control (Fig. 4d). As expected, BRCA2 knockdown increased sensitivity to olaparib, serving as a canonical HR-deficient reference. Notably, the extent of viability reduction observed upon dual depletion of PIKfyve and PIP5K1C was comparable to that seen with BRCA2 knockdown. Comment 8: PARPi resistance and re-sensitization – In Figure 7, the authors examine PARPi resistance by BRCA2 reversion, but there are quite a few known and different mechanisms that cells (especially cancer cells) can leverage to become more resistant to PARPi action. It would be interesting to see whether BRCA1/2 negative cells that have restored homologous recombination repair due to TP53BP1 loss, or resistance due to increased efflux pump expression, are re-sensitized to PARPi when treated with UNI418. Response: We appreciate the reviewer’s thoughtful suggestion. We fully agree that PARP inhibitor resistance can arise through multiple mechanisms, including TP53BP1 loss–mediated restoration of HR and drug efflux pump upregulation. Testing whether UNI418 re- sensitizes such models would indeed provide additional mechanistic insight. However, generating or obtaining TP53BP1-deficient BRCA1/2 mutant lines or efflux pump–overexpressing PARPi-resistant models, and validating their resistance mechanisms, is beyond the scope and technical feasibility of the current revision timeline. We will evaluate whether UNI418 could restore PARPi sensitivity to other types of resistant mechanisms in future study. Importantly, our study already demonstrates that UNI418 re-sensitizes PARPi-resistant cells driven by BRCA2 reversion, a clinically relevant resistance mechanism. Together with the consistent HR suppression shown in multiple independent assays (RAD51 foci, DR-GFP reporter, DDR signaling), our results strongly support the conclusion that UNI418 enhances PARPi sensitivity by targeting HR restoration. Comment 9: Big Picture – It is not clear within the discussion whether the authors think that their tool compounds can be modified for therapeutic purposes, and this would be helpful. I was also expecting some discussion about differences in IP and related biosynthetic 6 processes between normal and cancer cells, and between different cancer types that naturally would have plenty of metabolic variation given their context and specific genomic profile. Response: To address these points, we expanded the Discussion to incorporate broader therapeutic implications of UNI418 and to introduce biological differences in IP metabolism relevant 6 to cancer contexts. Specifically, we added a paragraph that discusses cancer-type– associated variation in IP biosynthetic enzymes and their potential influence on tumor 6 biology and treatment vulnerability: “In addition to these mechanistic findings, accumulating evidence suggests that IP6 metabolism itself may differ across cancer types. While UNI418 does not directly target IP6K or IPMK, dysregulation of these upstream enzymes has been associated with tumor biology and clinical prognosis. IP6K2 functions as a tumor suppressor in breast cancer, whereas IP6K1 upregulation correlates with aggressive recurrence and poor survival outcomes. These data suggest that distinct nodes within the inositol phosphate network are differentially exploited by malignancies. Tumors heavily dependent on HR and IP6 metabolic wiring may therefore be uniquely vulnerable to agents—such as UNI418—that reduce cellular IP pools. Future comparative metabolomic and genomic analyses across 6 tumor lineages will be essential for defining biomarkers that predict UNI418 sensitivity and guide clinical application. Taken together, these findings establish a mechanistic link between inositol phosphate signaling, HR dependency, and exploitable therapeutic vulnerabilities in DNA repair–dependent cancers, including those with BRCA dysfunction or PARPi resistance.” Comment 10: “DNA repair” – throughout this manuscript, the words “DNA repair” are used to actually refer to “DNA double strand break repair” or similar. The processes being discussed here are specific to that type of DNA damage in the context of DNA replication, and not all possible types of DNA damage that exist. Please amend all instances of that language to be specific. Response: Thanks for thoughtful comments. We fully agree that the term “DNA repair” was at times used in a broad manner, whereas the processes discussed in our study relate specifically to DNA double-strand break (DSB) repair mechanisms, particularly those occurring during DNA replication. To address this, we carefully revised the manuscript to ensure that terminology is used with appropriate specificity throughout. In all relevant sections—Introduction, Results, and Discussion—we replaced general references to “DNA repair” with more accurate terms such as “DNA double-strand break repair,” “DSB repair,” or “HR-dependent DSB repair,” depending on the context. Comment 11: Western blot loading control –In figure 1b, the appropriate loading control for pRPA32 is total RPA32 levels, please include this control. H3 is less ideal in the context of that experiment. Response: We agree that total RPA32 serves as a more appropriate loading control for pRPA32 analysis. To address the reviewer’s request, we additionally treated cells with CPT and HU and examined CHK1, p-CHK1, p-RPA32, and total RPA32 levels. The results indicate that CHK1, p-CHK1, and p-RPA32 were reduced in ML367-treated cells and further decreased upon UNI418 treatment, whereas total RPA32 levels remained unchanged (Fig 1d, 1e). In Extended Fig. 1b, we showed that 5-FUrd treatment decreased p- CHK1 and CHK1 in ML367-treated cells and further reduced p-CHK1 and CHK1 in UNI418-treated cells. Comment 12: How these inhibitors are referred to – generally it is advisable to be specific and call them PARP1/2-trapping inhibitors, as other small molecules that block PARP enzyme action exist, with no to variable impact on trapping PARP enzymes at sites of DNA leading to damage. Response: We agree that the term “PARP inhibitors” can be ambiguous, as it encompasses both catalytic inhibitors and clinically used agents that induce PARP1/2 trapping. To address this, the sentence in the Introduction has been updated to: “The approval of clinically used PARP1/2-trapping inhibitors (commonly referred to as PARP inhibitors, PARPis), such as Olaparib, Niraparib, Rucaparib, Veliparib, and Talazoparib, by the US FDA, marks a pivotal advancement in the treatment of breast and ovarian cancers carrying BRCA mutations.” We have applied this terminology consistently throughout the revised manuscript. Comment 13: Data normalization –In Figure 1a, it is not clearly stated whether the Luc-ATAD5 data is normalized or not. The authors should revise all figures and clearly state whether the data is normalized, and if so, what the data is normalized to. Response: In Figure 1a, the Luc-ATAD5 activity was normalized to the NT (non-treated) control, which was set to 1, and all other values are presented as relative fold changes. We have now clarified this in the figure legend. We also carefully reviewed other figures and added explicit descriptions of normalization methods in the corresponding legends wherever necessary to ensure consistency and transparency in data presentation. Comment 14: Phosphorylation of CHK1 – I would suggest including the blot of phospho-CHK1 in the main body of the manuscript in figure 1. Response: In accordance with the comment, we have moved the phospho-CHK1 blot into the main Figure 1d. Additionally, based on comments from other reviewers, we repeated the experiments under multiple conditions, including ATR inhibitor treatment, to more comprehensively assess CHK1 phosphorylation dynamics. The revised figure now reflects these updated and expanded datasets. Comment 15: Kinase screen – I suggest the authors include extended data figure 2 in the main body as it guides the narrative of the study. I would also ask for more details on what precent control is referring to, and that the authors label the kinases of interest within the plot to make it more clear to the reader. Response: In accordance with the comment, the kinase screening data previously shown in Extended Data Fig. 2a has been moved into the main figure panel (now Fig. 2a) to better support the flow of the manuscript. To clarify the definition of “percent control,” we have added the following explanation in the figure: “Percent Control = (Signal with UNI418 / Signal with DMSO) × 100. Kinases showing 0 ≤ x < 10% control are highlighted (22 kinases in total).” We also considered highlighting or labeling the kinases of interest directly within the plot. However, due to the large number of kinases and the limited figure size, adding individual labels significantly reduced overall readability. Therefore, instead of labeling them within the plot, we have listed the names of the 22 kinases (0–10% control group) below the figure for clarity. Comment 16: Figure 2A is missing axis labels, please include these. Response: In the revised manuscript, we regenerated the graph using Prism to improve overall clarity and readability and added the appropriate axis labels. The updated graph is now presented as Fig. 2b. Comment 17: Surface plasmon resonance – In figure 2B, there is no description of what the black lines underneath the colored lines represent. Please describe what these are or remove them. Response: In Fig. 2b (now Fig. 2c), the black lines represent the predicted fitted curves generated from the kinetic binding model used for SPR analysis. We have added a clear explanation of this in the figure legend of the revised manuscript. “c, The kinase domains of MBP-tagged PIP5K1C and PIKfyve were immobilized to the CM5 chip. SPR was carried out after injecting UNI418. The black curves indicate the model-predicted fits corresponding to the experimental sensorgrams shown in color.” Comment 18: The methods section describes two cell viability assays, but it is not clear in the figure which one is used for each dataset. Please include this information within the appropriate figure legends. It is also not clear why two different cell viability assays need to be used Response: In our study, we used two complementary cell viability assays — the CellTiter-Glo assay and the clonogenic survival assay — to assess short-term metabolic viability and long- term proliferative capacity, respectively. We have now clearly indicated in each figure legend which assay was used for the corresponding dataset. Comment 19: Representative images of clonogenic cell survival assays – When appropriate, I would appreciate the if the authors included representative images of their cell survival assays, specifically clonogenic cell survival assays. Response: In accordance with the request, we have added representative images of the clonogenic survival assays to the revised manuscript (now included in Extended Data Fig. 8b). Comment 20: CUL4A neddylation – Figure 5a and 5b are missing a control that clearly demonstrates that the higher molecular weight CUL4A band is clearly CUL4A-Nedd. The authors should include a blot demonstrating that this band does not appear in the presence of an inhibitor of neddylation such as the compound MLN4924 used in reference 39. Response: In response, we performed additional experiments by including a treatment group with the neddylation inhibitor MLN4924. As shown in the revised figure, the higher–molecular weight CUL4A band disappears upon MLN4924 treatment, confirming that this band indeed represents the neddylated form of CUL4A. This new data has been added to the updated version of Fig. 5a. Comment 21: I would recommend the authors merge the graphs in extended data 9C and use dash lines to represent additional treatments. Response: As recommended, we have merged the graphs in Extended Data Fig. 9c and used dashed lines to represent the additional treatment conditions. These changes have been incorporated into the revised figure (now included in Extended Data Fig. 9c). Comment 22: IPPK siRNA – The authors did not include a control demonstrating the effectiveness of their siRNA against IPPK. Response: To address this concern, we performed RT–qPCR analysis to evaluate the knockdown efficiency of IPPK following siRNA treatment. The results confirming effective depletion of IPPK mRNA have been added to the revised manuscript (now included in Extended Data Fig. 9f). Comment 23: In figure 6C, the authors make the claim that silencing WDR or CUL4A causes resistance to Olaparib, but only shows comparison compared to vehicle controls. To support this claim, please show the results of the statistical test between the different siRNAs at 20 µM and 40 µM Olaparib. Response: In accordance with the suggestion, we have reanalyzed the data and performed statistical comparisons between the siRNA treatment groups (siWDR5 and siCUL4A) and the control siRNA at both 20 µM and 40 µM Olaparib. The updated statistical analyses are now reflected in the revised Fig. 6c, and the corresponding significance values have been added to the figure. Reviewer #3 and #4 Comment 1: The introduction should include the background of ATAD5. The authors state that ML367 was identified in 2010 and shown to increase ATAD5 protein levels under replication stress. Since UNI418 is a derivative of ML367, these facts, as well as the functional relevance of ATAD5 stabilization, should be included. Is it generally accepted that ATAD5 stabilization reflects replication stress? Response: In response, we have revised the Introduction to include background information regarding ATAD5 biology, its relevance to replication stress, and the historical connection between ML367 and UNI418. Specifically, we added the following paragraph to provide conceptual context: “ATAD5 (also known as ELG1 in yeast) is an essential PCNA unloader that maintains genome stability during DNA replication. Loss or depletion of ATAD5 results in persistent PCNA retention on chromatin, replication fork stalling, and elevated replication stress, ultimately contributing to genomic instability and tumorigenesis 19. Importantly, ATAD5- luciferase expression of the reporter cell line is markedly induced under replication stress, and this increase has been widely used as an established molecular marker for replication stress responses 20. In 2010, we reported that a small molecule ML367 selectively suppresses the elevation of ATAD5-luciferase protein levels in the reporter cell under replication stress conditions 21.” Comment 2: • The authors used 5-FU for 16–24 hours to induce replication stress. However, 5-FU is not a standard agent for inducing replication stress in cancer cells, and indeed pRPA32 was only modestly increased (Fig. 1d). Would similar results be obtained with other established replication stress inducers such as HU or camptothecin? • I recommend including supplementary data using alternative replication stress– inducing drugs to validate the conclusion that UNI418 represses replication stress. Response: We agree that 5-FUrd is not the most commonly used replication stress inducer and understand the reviewer’s concern regarding p-RPA32 signal intensity. In response, we performed additional experiments using two well-established replication stress agents, hydroxyurea (HU) and camptothecin (CPT). Cells were treated with HU or CPT, followed by ML367 or UNI418 exposure, and we examined CHK1, p-CHK1, p-RPA32, and total RPA32 levels. Consistent with our original 5-FUrd data, HU and CPT treatment revealed that CHK1, p-CHK1, and p-RPA32 were reduced by ML367 and further decreased by UNI418, while total RPA32 remained unchanged. These results confirm that UNI418 suppresses replication stress signaling across multiple replication-blocking agents. The newly obtained HU and CPT data have been incorporated as Fig. 1d and 1e in the revised manuscript. Comment 3: • In Fig. 1d and e, the blot for total RPA2 should be shown. The CHK1 blot from Extended Data Fig. 1b could be moved to the main figure because it is the key point of Figure 1. Response: Thanks for the suggestion. Fig. 1d and 1e are now presented with newly generated HU- and CPT-based replication stress experiments, and these panels include total RPA32 blots to provide appropriate loading controls. Regarding the CHK1 and p-CHK1 results originally shown in Extended Data Fig. 1b under 5-FUrd treatment, we retained these data in the extended section because HU and CPT experiments now occupy the corresponding position in the main figure panels. Therefore, the expanded CHK1 and p-CHK1 blots under 5-FUrd treatment are presented in the updated Extended Data Figure, while Figures 1d and 1e in the main manuscript focus on HU and CPT-based stress responses. Comment 4: • Fig. 2a: The x-axis should be annotated. Response: Sorry not to provide better graph in the original submission. We have improved the quality of Fig 2d (now Fig. 2b) by replacing the original graph which was provided by the company with a newly generated version using GraphPad Prism with actual dataset, which now includes clear X- and Y-axis labels, error ranges and higher graphical clarity. Comment 5: • Fig. 2d: The phosphatidylinositol pathway may be unfamiliar to many readers primarily interested in DNA damage responses and PARPi. A schematic explaining the relationships among PIKfyve, PI(3)P, PI(3,5)P2, and related molecules would be helpful. Response: To address this, we have added a schematic diagram illustrating the enzymatic relationships among PIKfyve, PI(3)P, PI(3,5)P₂, and related inositol phosphates. This schematic has been incorporated into the revised Fig. 2e to aid understanding of how UNI418 interacts with lipid kinase signaling pathways. Comment 6: • Fig. 3a: The authors report that RAD51, CHK1, and CtIP are downregulated upon UNI418 treatment. However, RAD51 remains at a detectable level. o I strongly recommend performing a quantitative proteomic analysis to determine how many proteins are affected by UNI418. Is RAD51 one of a few or one of many targets? Response: To address whether UNI418 broadly affects the proteome or selectively targets specific proteins, we conducted SILAC-based quantitative mass spectrometry in an independent validation experiment. The analysis indicated that UNI418 does not cause global protein degradation but instead affects a restricted subset of proteins. Notably, several replication-associated and chromatin-regulatory proteins, including MCM2, MCM5, MCM6, MCM7, and UHRF1, were consistently reduced upon UNI418 treatment. In contrast, RAD51 was not quantified in this dataset due to insufficient peptide coverage, likely reflecting low abundance and technical limitations of the LC–MS/MS run rather than lack of biological regulation. These results support our conclusion that UNI418 does not induce nonspecific proteolysis but instead modulates a defined set of proteins linked to DNA replication and genome stability. Because these SILAC data were performed as supportive validation and are not essential for the central conclusions of the manuscript, we did not include them in the revised figures. Nevertheless, we are happy to provide the data to the editor or reviewers upon request. Furthermore, we plan to reveal other proteins targeted by UNI418 using WDR5 interacting protein upon UNI418 treatment under proteasome inhibition. However, due to time limit for revision, constructing WDR5-BioID with inducible manner was not feasible. We plan to explore this direction in future. Comment 7: o The reduction in RAD51 should also be quantified from immunoblots and immunofluorescence (total levels, not just foci, if measurable). Response: As recommended, we performed quantitative analysis of RAD51 protein levels: - Western blot band intensities were quantified using ImageJ across ≥3 independent experiments. - RAD51 immunofluorescence (total nuclear signal, not only foci) was quantified using ZEN software. Both analyses consistently show a significant reduction in RAD51 upon UNI418 treatment. These quantifications have been added to the revised Fig. 3b and corresponding Extended Data Fig. 6b. Comment 8: o Please also consider the literature: heterozygosity of key HR genes (RAD51, BRCA1/2) often does not produce strong phenotypes. For example, comparisons to RAD51+/- versus -/- (or BRCA1+/- vs. BRCA1-/-) cells can be found elsewhere. Response: We have included additional discussion comparing our findings to known RAD51+/− and BRCA1+/− phenotypes. We believe that partial reduction rather than complete loss of RAD51 protein following UNI418 treatment causes mild but significant HR defect due to: - concurrent degradation of multiple HR regulators (RAD51, CHK1, CtIP), - UNI418 reduces RAD51 little more than half compared to RAD51+/-, - Cul4A activation amplifying proteolysis, - the requirement for precise stoichiometry in HR machinery. This explanation has been added in the Discussion to contextualize the observed phenotype. Comment 9: • Fig. 3b: A statistical analysis of UNI418 alone versus UNI418 + IR is warranted, as the remaining RAD51 foci formation appears different from the general BRCA1/2-deficient phenotype (no RAD51 foci formed). Response: As requested, we performed statistical analysis comparing the control, UNI418, IR, and UNI418 + IR conditions. Quantification of RAD51 foci in EdU-positive nuclei showed: - Control: ~6 foci - UNI418 alone: ~4 foci - IR (1 h): ~30 foci - UNI418 + IR (1 h): ~14 foci These analyses confirm that IR induces robust RAD51 foci formation, and that UNI418 reduces the number of IR-induced foci to an intermediate level. Statistical comparisons have been added to the revised figure, and the manuscript text has been updated accordingly. Comment 10: • Fig. 3c could be moved to Extended Data. Response: In accordance with this recommendation, Figure 3c has been moved to Extended Data Fig. 6c in the revised manuscript. Comment 11: • Fig. 3f: The reduction in HR frequency with UNI418 is much milder than with siRAD51. Please provide immunoblots of RAD51 under UNI418 and siRAD51 for comparison. Response: As requested, we have provided immunoblots comparing RAD51 protein levels under UNI418 treatment and siRAD51 knockdown, now included in Extended Data Fig. 7c. Consistent with the observed differences in HR frequency, siRAD51 almost completely depleted RAD51 protein, whereas UNI418 treatment resulted in a partial reduction, leaving a detectable residual level of RAD51. This difference in RAD51 depletion efficiency explains why the reduction in HR frequency by UNI418 appears milder than that observed with siRAD51. Comment 12: • Fig. 3g: “parp1-/-” should be capitalized as “PARP1-/-” since it refers to the human gene knockout. Response: Thanks for the comment. The notation has been corrected from parp1-/- to PARP1-/- throughout the manuscript, including in Figure 3g. Comment 13: • Fig. 3g and 3i: The authors used 0.25 µM UNI418, described as non-toxic to both cell types. If UNI418 is a catalytic inhibitor, why does its toxicity display clear dose dependence in PARP1-/- cells? Does RAD51 protein level also show dose-dependency by UNI418? o I am concerned that the apparent hypersensitivity of PARP1-/- cells by a dose-dependent UNI418 (1-5 uM >>0.25 uM) could reflect off-target effects, such as induction of PARP1-dependent DNA damage (base damage?). o Please include dose–response experiments (0, 0.25, 0.5, 1, 2.5, 5 µM) to clarify this issue. Response: To address the concern, we performed dose–response analyses of UNI418 (0, 0.25, 0.5, 1, 2.5, 5 µM) in both HCT116 WT and HCT116 PARP1-/- cells and examined RAD51, CHK1, CtIP, CUL4A, and γH2AX levels by immunoblotting (now included in Extended Data Fig. 8a). RAD51, CHK1, and CtIP showed a clear dose-dependent reduction in both WT and PARP1-/- cells. This pattern is consistent with our model in which UNI418 inhibits PIKfyve/PIP5K1C, decreases IP levels, and enhances Cul4A-mediated proteolysis of HR 6 factors. Importantly, the reduction is gradual rather than abrupt or irregular, which does not support an off-target toxicity effect. A dose-dependent increase in γH2AX was observed in PARP1-/- cells, and the magnitude was significantly higher than in WT cells. This heightened sensitivity is expected because PARP1-/- cells rely more heavily on HR to resolve replication-associated DNA damage; therefore, additional UNI418-mediated suppression of HR proteins leads to greater accumulation of DNA breaks. Together, these results support that the hypersensitivity of PARP1-/- cells reflects their increased dependence on HR rather than off-target toxicity of UNI418. Comment 14: • Fig. 4a: Since CHK1 is markedly reduced, its role in the drug sensitivity data must be considered. CHK1 inhibition is known to synergize with PARPi because PARPi-induced replication stress activates the ATR–CHK1 pathway. The authors should evaluate whether CHK1 suppression contributes to the observed olaparib sensitivity. Response: We agree with the reviewer that CHK1 plays a critical role in the cellular response to replication stress and that pharmacological or genetic suppression of CHK1 has been reported to synergize with PARP inhibition. PARPi-induced replication stress activates the ATR–CHK1 signaling axis, and inhibition of CHK1 compromises S-phase checkpoint control, leading to replication fork collapse and enhanced cytotoxicity. In our study, UNI418 treatment leads to a reduction in CHK1 protein levels concomitant with depletion of other HR-associated factors, including RAD51 and CtIP (Fig. 4a,b). We therefore acknowledge that CHK1 suppression is likely to contribute to the enhanced sensitivity to olaparib observed upon UNI418 treatment. However, several lines of evidence suggest that this effect cannot be attributed solely to CHK1 loss. First, UNI418 induces concurrent destabilization of multiple HR regulators rather than selectively targeting CHK1. Second, UNI418 markedly suppresses RAD51 foci formation and HR reporter activity, indicating a direct impairment of homologous recombination capacity. Third, the absence of additive effects between UNI418 treatment and genetic depletion of PIKfyve/PIP5K1C supports a shared upstream mechanism involving IP -dependent 6 Cul4A activation rather than isolated checkpoint inhibition. Taken together, our findings are consistent with a model in which UNI418-induced CHK1 reduction contributes to olaparib sensitivity as part of a broader HR-defective state, rather than acting as the sole driver of drug synergy. We have revised the Discussion to explicitly acknowledge the contribution of CHK1 suppression and to contextualize our results within the established ATR–CHK1–PARP interaction framework. Comment 15: • Fig. 4d: The sensitivity observed is mild (y-axis begins at 60%). HR-deficient cells are typically hypersensitive to olaparib at low micromolar or even nanomolar concentrations. o Please add control data for siBRCA1, siBRCA2, or siRAD51 cells for comparison. o The addition of UNI418 in these knockdown experiments (e.g., siPIKfyve + UNI418) would be informative. Response: To address this point, we performed additional experiments using siBRCA2 as HR- deficient control (Fig. 4d). As expected, BRCA2 knockdown increased sensitivity to olaparib, serving as a canonical HR-deficient reference. Notably, the extent of viability reduction observed upon dual depletion of PIKfyve and PIP5K1C was comparable to that seen with BRCA2 knockdown. We also examined whether UNI418 further enhances sensitivity when combined with siPIKfyve, siPIP5K1C, or the double knockdown (Fig. 4d). Interestingly, UNI418 treatment alone reduced viability to a similar extent, and additional knockdown of PIKfyve, PIP5K1C, or both did not further sensitize cells beyond the effect of UNI418 alone. These results suggest that the sensitizing effect of UNI418 and the combined depletion of PIKfyve/PIP5K1C converge on the same pathway, reflecting a shared mechanism involving decreased IP and consequent reduction of HR protein stability. 6 Comment 16: • Fig. 5a–b: The quantification is problematic. The Actin loading control is uneven, and the differences are marginal. Consider removing these panels if your conclusions remain supported without them. Response: In response to this concern—and consistent with similar comments from other reviewers—we repeated the experiments in Fig. 5a, including three independent biological replicates, and replaced the original panels with newly generated data. To verify that the upper CUL4A band represents the neddylated form, we additionally included MLN4924, a well-characterized neddylation inhibitor. As expected, MLN4924 treatment eliminated the upper band, confirming its identity as CUL4A–Nedd. Furthermore, we optimized sample loading and exposure conditions to ensure uniform Actin loading controls and clearer quantification across all replicates. The updated blots and quantification now show a consistent and reproducible reduction in CUL4A neddylation upon UNI418 treatment. Thus, with the improved data quality and proper validation using MLN4924, we believe these panels provide meaningful mechanistic support and have retained them in the revised manuscript. Comment 17: Please illustrate a pathway for how excess IP6 diminishes Cul4A neddylation Response: To address this point, we have revised the hypothetical model presented in Fig. 7j. Accordingly, we have added the following description to the figure legend of Fig. 7j: “Lipid kinases, such as PIKfyve and PIP5K1C, regulate cellular IP6 levels through the phosphatidylinositol signaling pathway. IP6 suppresses Cul4A ubiquitin ligase activity by promoting its deneddylation (N8) by the COP9 signalosome (CSN), thereby stabilizing key HR proteins such as RAD51 and CHK1.” Comment 18: • Fig. 5b: There is no additive effect of PIP5K1C knockdown and PIKfyve knockout, which appears inconsistent with Fig. 4d. Please discuss. Response: Although double depletion of PIKfyve and PIP5K1C results in a stronger reduction in cell viability compared to the single knockdowns (Fig. 4d), this additive effect is not reflected at the level of CUL4A neddylation (Fig. 5b). There are several biological reasons why these observations are not inconsistent. First, CUL4A neddylation appears to behave as a threshold- or saturation-type response. Our data indicate that knockdown of either PIKfyve or PIP5K1C alone is already sufficient to reduce IP6 to a level that maximally triggers CUL4A de-neddylation. As such, additional depletion of the second kinase may not further increase the magnitude of this biochemical readout. In contrast, cell viability represents a downstream, cumulative phenotype that integrates multiple layers of replication stress and impaired HR repair. Therefore, even if CUL4A de- neddylation does not further decrease beyond a threshold, the combined depletion of both kinases exacerbates cellular stress and leads to a more pronounced loss of viability. Taken together, the absence of an additive effect in CUL4A neddylation is consistent with a saturable mechanistic response upstream, whereas the stronger viability defect reflects downstream amplification of replication stress and HR deficiency. We have added this explanation to the revised manuscript. Comment 19: • Fig. 5c: RAD51, CHK1, and CtIP levels increase under siCUL4A, but also under UNI418 treatment. The authors should provide an unbiased interpretation. Response: We agree that the interpretation of Fig. 5c should be clearly described. siCUL4A alone increases RAD51, CHK1, and CtIP levels compared with control (C), consistent with the role of CUL4A as an E3 ligase promoting proteolysis of these proteins. UNI418 alone decreases RAD51, CHK1, and CtIP levels compared with control, in line with our model that UNI418 enhances Cul4A-dependent degradation of HR factors. When UNI418 and siCUL4A are combined, HR protein levels are elevated compared with UNI418 alone but do not fully return to the siCUL4A-only levels. We interpret this partial rescue as a consequence of incomplete depletion of CUL4A protein by siRNA treatment. Consistent with many E3 ligases, even modest residual amounts of CUL4A can retain biological activity. Thus, partial knockdown likely limits the extent to which CUL4A- dependent proteolysis can be fully suppressed, resulting in an incomplete recovery of HR protein levels under UNI418 treatment. Comment 20: • Fig. 6c: In siCtl cells, olaparib induces 20–40% cell death at 20–40 µM. Since the MOA of olaparib in HR-proficient cells is PARP trapping, these results need further explanation. How can siCUL4A or related treatments “rescue” HR-proficient cells? Excess RAD51 alone is unlikely to confer “super-HR” proficiency. Please consider alternative interpretations. Response: We note that olaparib can induce measurable cell death even in HR-proficient cells due to PARP1 trapping. The 20–40% decrease in viability in siCtrl cells at 20–40 µM olaparib is therefore consistent with the well-established cytotoxicity of PARP-trapping lesions in otherwise HR-competent cells. Importantly, the apparent “rescue” observed in siCUL4A cells should not be interpreted as enhanced HR capacity (“super-HR”). Instead, our data suggests an alternative explanation: CUL4A depletion partially alleviates replication-associated stress that is exacerbated by PARP trapping. Because CUL4A promotes proteolysis of several replication- and repair- associated proteins, its knockdown increases steady-state levels of multiple factors involved in maintaining replication fork stability. This general increase in replication- supporting proteins likely provides a modest buffering effect against PARP-trapping– induced stress, resulting in slightly improved survival relative to siCtrl. Thus, the reduced sensitivity to olaparib in siCUL4A cells does not reflect enhanced HR per se, but rather a broader dampening of replication stress via reduced CUL4A- mediated proteolysis. We have revised the manuscript to clarify this interpretation and avoid overstatement of HR dependence. Comment 21: • Fig. 7d, e, g, h: C4-2 and C2-2 cells (HR-proficient due to BRCA reversion mutations) are unexpectedly more sensitive to treatment. Please clarify why. Response: Although C4-2 and C2-2 cells restore BRCA2 function through reversion mutations and are categorized as HR-proficient, multiple studies have shown that BRCA-reverted cancer cells do not fully regain the genomic stability of genuinely HR-proficient cells. Instead, they retain elevated levels of replication stress and persistent genomic instability due to accumulated mutations and chromosomal rearrangements that arise prior to reversion. As a consequence, BRCA-reverted tumor cells remain highly dependent on robust HR and replication-stress response pathways for survival. Because UNI418 induces Cul4A-mediated degradation of essential HR factors—including RAD51, CHK1, and CtIP—the HR capacity of BRCA-reverted cells is disproportionately compromised upon UNI418 treatment. This heightened reliance on HR makes C4-2 and C2-2 cells more vulnerable to UNI418 compared with their parental BRCA2-deficient PEO-1 and Capan-1 cells. Consistent with this interpretation, UNI418 treatment led to a marked increase in apoptotic cell death specifically in C4-2 cells (Fig. 7i). This mechanistic vulnerability also explains why the combination of UNI418 and Olaparib produced stronger synthetic lethality in BRCA-reverted cells relative to parental lines. We have included this explanation in the revised manuscript. Comment 22: • As the authors noted in the Introduction, the synthetic lethality between PARP deficiency and BRCA1/2 deficiency is commonly explained by ssDNA gap accumulation, fork reversal, and transcription–replication collisions. To reproduce these effects, genuine HR deficiency together with PARP catalytic inhibition is required. Importantly, PARP catalytic inhibition is fully achieved at concentrations below 1 µM olaparib. However, the data shown in Figure 7 demonstrate a dose-dependent effect of olaparib in the range of 1–10 µM, which is unlikely to reflect catalytic inhibition but rather PARP trapping. This makes the apparent effectiveness of the UNI418 and PARP-/- combination difficult to interpret. Given that the precise mechanism of action of PARP inhibitors, particularly in BRCA-deficient backgrounds, remains controversial, the authors should avoid attributing their findings solely to PARP inhibition. Additional testing with DNA-damaging agents such as camptothecin or cisplatin would help to substantiate whether the observed effects indeed arise from HR defects. Response: We appreciate the reviewer’s detailed mechanistic insight. We agree that PARP catalytic inhibition is largely saturated at concentrations below 1 µM olaparib, and therefore the dose-dependent effects observed at 1–10 µM in Fig. 7 primarily reflect PARP–DNA trapping activity rather than catalytic inhibition alone. In the revised manuscript, we have clarified that the observed synthetic lethality between UNI418 and olaparib should not be interpreted exclusively through catalytic inhibition mechanisms. Importantly, our central conclusion—that UNI418 restores vulnerability in PARPi-resistant or BRCA-reverted cells by compromising HR capacity—does not rely solely on PARP inhibition. Multiple independent lines of evidence support HR impairment by UNI418: - UNI418 drives Cul4A-dependent degradation of RAD51, CHK1, and CtIP, leading to HR factor depletion (Fig. 3a; Extended Fig. 6). - RAD51 foci formation after IR is strongly suppressed by UNI418, particularly in S-phase cells (Fig. 3b). - HR reporter assays confirm significant loss of HR activity following UNI418 treatment (Fig. 3e). - UNI418 enhances γH2AX accumulation in PARP1–/– cells, consistent with increased DSB burden in HR-defective backgrounds (Extended Fig. 8a). In addition, to address the reviewer’s concern about whether UNI418-induced cellular responses extend beyond olaparib-specific contexts, we performed biochemical validation using alternative replication stress inducers. CPT or HU treatment revealed that CHK1, p-CHK1, and p-RPA32 levels decreased with ML367 and were further reduced with UNI418, while total RPA32 remained unchanged (Fig. 1d and e). These findings demonstrate that UNI418 suppresses replication stress signaling independent of PARP inhibitor exposure, further supporting our HR-defect model. Although we did not extend CPT or cisplatin experiments to full viability assays, we believe that the combined biochemical and functional data—spanning protein stability, RAD51 dynamics, foci formation, HR reporter output, and replication stress signaling—provide a strong mechanistic foundation for attributing UNI418 efficacy to HR pathway disruption rather than PARP-specific responses. Dear Editor and Reviewers, We have carefully addressed all remaining concerns and suggestions raised by the reviewers, and the manuscript has been revised accordingly. Detailed point-by-point responses are provided below. Reviewer #2 We sincerely thank you for your careful evaluation of our revised manuscript and for your constructive and supportive comments. We appreciate your recognition that the additional data and revisions have improved the study, and we are grateful for your specific suggestions to further strengthen clarity and presentation. We have now revised the manuscript accordingly and addressed all your remaining points. • Known abbreviations such as DSB are now defined at their first occurrence in the text. • The minor punctuation issue you noted (“by the FDA marks”) has been corrected. • Regarding your suggestion to briefly describe the target of Apilimod, we would like to note that this information was already stated earlier in the Results section (page 9, line 26 in the revised manuscript), where Apilimod is explicitly described as a PIKfyve inhibitor. • As suggested, we have added clarifying statements to the relevant figure legends indicating that the numbers shown above western blot bands represent quantified signal intensities normalized to the appropriate loading controls. • We have also included experimental confirmation of PARP1 loss in the HCT116 PARP1−/− cells, as requested (Extended Data Fig. 7d). All corresponding changes in the revised manuscript are marked in red text for clarity and ease of review. We thank you again for your helpful feedback, which has significantly improved the quality and clarity of our manuscript. Reviewer #4 We thank the reviewer for this important comment regarding the interpretation of Fig. 4d and the strength of olaparib sensitivity in BRCA2-depleted cells. We agree that the degree of sensitivity observed in the original CellTiter-Glo assay (72- hour treatment) appeared modest compared to the well-established hypersensitivity of bona fide BRCA2-deficient cells to PARP inhibitors. We note that the original experiment measured short-term metabolic viability after 3 days of drug exposure, which can underestimate long-term clonogenic cell death and primarily reflects proliferation and metabolic activity rather than sustained survival. To directly address this concern, we performed additional clonogenic survival assays using siBRCA2-treated cells under prolonged olaparib exposure (7-day growth). Under these conditions, BRCA2 knockdown cells showed strong hypersensitivity to olaparib, with more than 50% reduction in colony formation even at low olaparib concentrations, consistent with canonical HR-deficient responses to PARP inhibition. Importantly, when we performed the same clonogenic assay for siPIKfyve, siPIP5K1C, and double knockdown conditions, the overall response pattern was consistent with the CellTiter-Glo results, supporting the relative interpretation presented in Fig. 4d. These new clonogenic data are now provided in Extended Data Fig. 8d. We have revised the manuscript to clarify the differences between the CellTiter-Glo viability assay and the clonogenic survival assay and to note that the clonogenic data confirm robust Olaparib hypersensitivity in BRCA2-depleted cells."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors made a complete revision of the manuscript They answer to all my point", "reviewer_2": "In the revised version of the manuscript by Lee et al., the authors thoroughly addressed most of my concerns. With inclusion new data and revisions, I agree that carrying out a cell cycle resolved time course to monitor foci of different DSBs falls outside the scope of the study. We appreciate the authors stating they will address investigating re-sensitization of other mechanisms of PARPi-resistance in a future study. We have caught a few minor text edits and suggestions that ideally should be addressed to ensure the final version of the study is the best it can be. 1. There are a few undefined abbreviations in the text: for example, “DSB” needs to be defined at its first instance of used, page 4 on line 11. 2. “… by the FDA, marks …” Line 20, remove the comma between FDA and marks. 3. On page 9, line 32, we suggest the author includes a brief description of the target(s) of Apilimod to help better inform and orient the reader to the authors main points. 4. We appreciate the author including the quantification of western blot signal in the relevant figures. As a point of clarity for the reader, we suggest they include in the figure caption of the relevant figures that the numbers above the band represent signal quantification of the band in reference to the appropriate loading control. 5. Regarding the HCT116 PARP1-/- cells used in this study, we would appreciate if the authors included a western blot or used another method to confirm the loss of the PARP1 protein in this cell line.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "I appreciate the authors’ efforts to address the reviewers’ comments and to include additional experiments in the revised manuscript. However, I remain concerned about the interpretation of Fig. 4d, which I believe requires further consideration. In Fig. 4d, siBRCA2 is presented as a canonical HR-deficient positive control for olaparib sensitivity. However, under the current experimental conditions, BRCA2 knockdown results in only ~20% reduction in viability even at 10 µM olaparib. This degree of sensitivity is unexpectedly mild for HR-deficient cells and does not align with the well-established hypersensitivity of bona fide BRCA2-deficient cells to PARP inhibitors, which typically manifests at low micromolar or even sub-micromolar concentrations. This raises the question of whether bona fide cell death is occurring under these conditions, or whether the observed effect instead reflects a modest slowing of cell-cycle progression or proliferation. In this context, it is difficult to interpret the data as measuring the canonical cytotoxic effect of olaparib in HR-deficient cells. Given this limited response, it is difficult to consider the siBRCA2 condition in Fig. 4d as a robust or appropriate positive control for HR deficiency. As a consequence, the conclusion that dual depletion of PIKfyve and PIP5K1C produces an effect “comparable to BRCA2 knockdown” is not fully convincing.I therefore strongly encourage the authors to further optimize or reconsider the experimental conditions used in Fig. 4d (e.g., efficiency of BRCA2 depletion, drug concentration range, assay sensitivity, or choice of HR-proficient cells)."}, "author_response": "Dear Editor and Reviewers, We have carefully addressed all remaining concerns and suggestions raised by the reviewers, and the manuscript has been revised accordingly. Detailed point-by-point responses are provided below. Reviewer #2 We sincerely thank you for your careful evaluation of our revised manuscript and for your constructive and supportive comments. We appreciate your recognition that the additional data and revisions have improved the study, and we are grateful for your specific suggestions to further strengthen clarity and presentation. We have now revised the manuscript accordingly and addressed all your remaining points. • Known abbreviations such as DSB are now defined at their first occurrence in the text. • The minor punctuation issue you noted (“by the FDA marks”) has been corrected. • Regarding your suggestion to briefly describe the target of Apilimod, we would like to note that this information was already stated earlier in the Results section (page 9, line 26 in the revised manuscript), where Apilimod is explicitly described as a PIKfyve inhibitor. • As suggested, we have added clarifying statements to the relevant figure legends indicating that the numbers shown above western blot bands represent quantified signal intensities normalized to the appropriate loading controls. • We have also included experimental confirmation of PARP1 loss in the HCT116 PARP1−/− cells, as requested (Extended Data Fig. 7d). All corresponding changes in the revised manuscript are marked in red text for clarity and ease of review. We thank you again for your helpful feedback, which has significantly improved the quality and clarity of our manuscript. Reviewer #4 We thank the reviewer for this important comment regarding the interpretation of Fig. 4d and the strength of olaparib sensitivity in BRCA2-depleted cells. We agree that the degree of sensitivity observed in the original CellTiter-Glo assay (72- hour treatment) appeared modest compared to the well-established hypersensitivity of bona fide BRCA2-deficient cells to PARP inhibitors. We note that the original experiment measured short-term metabolic viability after 3 days of drug exposure, which can underestimate long-term clonogenic cell death and primarily reflects proliferation and metabolic activity rather than sustained survival. To directly address this concern, we performed additional clonogenic survival assays using siBRCA2-treated cells under prolonged olaparib exposure (7-day growth). Under these conditions, BRCA2 knockdown cells showed strong hypersensitivity to olaparib, with more than 50% reduction in colony formation even at low olaparib concentrations, consistent with canonical HR-deficient responses to PARP inhibition. Importantly, when we performed the same clonogenic assay for siPIKfyve, siPIP5K1C, and double knockdown conditions, the overall response pattern was consistent with the CellTiter-Glo results, supporting the relative interpretation presented in Fig. 4d. These new clonogenic data are now provided in Extended Data Fig. 8d. We have revised the manuscript to clarify the differences between the CellTiter-Glo viability assay and the clonogenic survival assay and to note that the clonogenic data confirm robust Olaparib hypersensitivity in BRCA2-depleted cells."}]

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