these were highly penetrant and relatively resistant to genetic background effects and additional molecular alterations. The use of preclinical
approaches to identify mechanisms of drug resistance alongside early-stage clinical trials provided further insights into the mechanism of
action of PARPi and revealed the basis of some
of the incomplete clinical responses to PARPi
in clinical trials (29, 30). Finally, a critical factor
in the rapid translation to the clinic of the SL
concept was the availability of potent drug-like
PARPi at the same time as the identification of
the BRCA SL (19, 20), highlighting the importance of medicinal chemistry and pharmacology
to the successful application of PARP/BRCA SL
and exemplifying how the convergence of otherwise distinct disciplines such as cancer genetics
and drug discovery can be effective.
Ideally, the design and interpretation of clinical
trials based on SL interactions should be based
on the biological hypothesis and robust preclinical
data. Although there is a direct link between the
recent approvals for PARPi in BRCA1/2-mutant
cancers and the original preclinical data identi-
fying the SL interactions over a decade ago, the
clinical development of PARPi as a SL approach
has not been straightforward. For example, a
purported PARPi, iniparib, failed to elicit the
expected clinical responses in a phase 3 trial,
despite showing potential in early-stage clinical
assessment (69). As a result, questions were raised
about the clinical potential of the entire drug class
and the SL approach in general (69). In retrospect,
the evidence supporting the mechanism of action
of iniparib as a PARPi was not compelling (69).
This reinforces the argument for the clinical de-
velopment of drugs to be informed by robust pre-
clinical biology. Of course, the preclinical and
clinical investigation of PARPi SL effect is far from
complete, and we highlight in Box 1 a series of
unanswered questions that, once addressed, could
guide the optimal use of PARPi in the future. For
example, a key observation has been that a fraction
(~15%) of ovarian cancer patients with BRCA1- or
BRCA2-mutant tumors continue to be disease free
more than 5 years after the initiation of PARPi
treatment (52). Understanding the underlying
reasons for these extended responses could help
in the design of both predictive markers and
Due to advances in technology, the system-
atic genome-wide identification of new SL inter-
actions has now been achieved in yeast (70), and
mapping each of the SL vulnerabilities asso-
ciated with cancer driver genes and oncogenic
processes in human cells is an ongoing activity;
this raises the possibility that additional cancer-
related SL interactions might be available for
therapeutic exploitation. Critical to these efforts
will be a greater understanding of the underly-
ing principles of what triggers an SL interaction,
the factors determining the robustness of such
interactions (i.e., how easily are SL interactions
reversed by other molecular changes), and how
robust SL interactions can be predicted, rather
than only empirically identified through large-
scale genetic screens. For example, it has been
suggested that robust SL interactions are enriched
for pairs of genes that are closely connected on
protein-protein interaction networks; i.e., those
that directly interact or interact via one or two
additional proteins or nodes, rather than being
distantly connected via a larger number of in-
tervening nodes (71). Likewise, proteins involved
in similar functions (often predicted from over-
lapping protein-protein interaction networks) are
hypothesized to have some shared SL inter-
actions, leading to the development of algorithms
that predict SL relationships (72). Integrating
functional genomics and proteomics with com-
putational network analysis approaches might
therefore be useful to dissect these principles with
the aim of streamlining the process of identifying
highly penetrant SL effects with potential ther-
It took more than 10 years from the discovery
of the PARPi/BRCA SL interaction to regulatory
approval. Now, based on preclinical studies recently published and currently under way, PARPi
remain a very active area of investigation. With
the number of ongoing clinical trials, there is
optimism that in the short term there will be
additional regulatory approvals for PARPi in multiple cancers. We suggest three broad areas, the
“holy trinity” of personalized cancer therapy research, that require further investigation: (i) Identifying who to treat. This can be achieved by
dissecting the mechanisms by which PARPi kill
or inhibit tumor cells and using this information
to develop refined, mechanism-based, biomarkers
that allow patient stratification. (ii) Combating
drug resistance. This can be achieved by identifying the mechanisms that cause PARPi resistance
and biomarkers that predict it, by understanding
how cancer heterogeneity and plasticity influence these processes, and by identifying clinical
approaches to delay or prevent the emergence
of the drug-resistant phenotype. (iii) Optimizing
combination therapy. This can be achieved by
understanding the mechanistic basis of why some
drug combinations have synergistic antitumor
effects, determining how drug combinations can
be used to target mechanisms of drug resistance,
and identifying predictive biomarkers of not only
single agent PARPi responses but also PARPi combination therapy responses.
If these issues can be addressed, we believe that
PARPi could eventually deliver considerable benefit to a substantial subset of cancer patients.
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Box 1. Some key unanswered questions about PARP inhibitors.
• What proteins beyond BRCA1 and BRCA2 contribute to the processing of trapped PARP1, the
drug’s key cytotoxic DNA lesion?
• How does the inability to repair a trapped PARP1 lesion at the replication fork translate into
• How do the roles of PARP1 in processes unrelated to DNA repair (e.g., inflammation, apoptosis,
immune system) influence the anticancer activity of PARPi?
• What is the relative predictive value of BRCA1, BRCA2 gene mutations or BRCAness biomarkers
for platinum and/or PARPi responses. What is the best way to measure BRCAness?
• What mechanisms distinguish “superresponders,” who show profound and sustained responses
to PARPi, from those who do not?
• What mechanisms operate clinically to drive development of resistance to PARPi in both
BRCA-mutant cancers and BRCAness cancers?
• How can PARPi be optimally used in combination therapies?