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RESEARCH POSTER PRESENTATION DESIGN © 2015
www.PosterPresentations.com
In pancreatic ductal adenocarcinoma (PDAC), mutations in
KRAS and deletion or promoter methylation of CDKN2A –
resulting in deregulation of the p16/CDK4/6/Rb axis – each
occur in over 90% of cases. Combination therapy approaches
targeting KRAS effectors and CDK4/6 may therefore be a
promising strategy for treatment in a majority of PDAC
patients. Lerociclib (G1T38) is an oral, potent, and selective
CDK4/6 inhibitor in clinical development as a potential
backbone for multiple combination regimens in cancer.
Preclinical and early clinical data have demonstrated that
lerociclib is differentiated based on its favorable
safety/tolerability profile and ability to be dosed continuously
with less dose-limiting neutropenia. The goal of this study
was to identify effective lerociclib-based drug combinations
and the associated biomarkers for PDAC treatment.
Introduction
Methods
• Lerociclib significantly enhances the response to PI3K or
ERK inhibition in a substantial proportion of tested
PDAC PDXs as measured by AUC analysis in the LTSA
platform.
• Differential gene expression analysis using PDAC PDX
RNA-seq data identifies gene enrichment signatures and
gene pathways associated with PDX model treatment
sensitivity.
• Validation of effective combinatorial treatment with
additional PDX models is underway and may support
clinical evaluation of lerociclib-based drug combinations
in PDAC.
Results
Lerociclib enhances the response to ERK
inhibition in a KRAS-mutant PDX model in vivo
Conclusions
• O'Leary B, Finn RS, Turner Nat Rev Clin Oncol. 2016
Jul;13(7):417-30.
• Roife, D., et al. Clinical Cancer Research, Mar. 2016.
• Bisi JE, Sorrentino JA, Jordan JL, Darr DD, Roberts PJ,
Tavares FX, Strum JC. Oncotarget. 2017 Jun 27
AcknowledgementsThis work was supported by G1 Therapeutics through sponsored
research agreement, Viragh Family Foundation, and NCI Cancer
Center Support Grant (P30CA016672)
We used an ex vivo drug screening platform, the live tissue
sensitivity assay (LTSA), to evaluate the ability of lerociclib
to synergize with 6 inhibitors of KRAS effectors across a
panel of 24 well-characterized PDAC patient-derived
xenografts (PDXs), including 20 PDXs with KRAS
mutations and 5 PDXs with co-occurring KRAS and
CDKN2A mutations. Ex vivo PDX responses to drug
combinations were analyzed alongside RNA-seq data to
identify gene signatures associated with tumor responses.
Drug combination synergies were further validated with in
vivo PDX models. Bioinformatic analyses were conducted
through correlation of gene expression with treatment
responses. GSEA-preranked pathway analysis was
conducted using ranked lists of genes from correlation
analyses.
Bingbing Dai1, Daniel M. Freed2, Jessica A. Sorrentino2, Jithesh Jose Augustine1, Christopher A. Bristow3, Caleb A. Class3, Tara G. Hughes1, Ya’an Kang1, Patrick J. Roberts2, Jason B. Fleming4,
and Michael P. Kim1
1Department of Surgical Oncology, UT MD Anderson Cancer Center, Houston TX; 2G1 Therapeutics, Research Triangle Park, NC; 3 Center for Co-clinical Trials, UT MD Anderson Cancer
Center, 4Department of Gastrointestinal Medical Oncology, Moffitt Cancer Center, Tampa, FL.
CDK4/6 inhibition with lerociclib enhances response to PI3K or ERK inhibitors in high-throughput, ex vivo pancreatic PDX screens
References
Identification of responder and non-responder PDX models to Lerociclib-based combinatorial treatments
Figure 2. Tumor tissue slices
were treated with 0.3 µM, 1
µM, and 3 µM of lerociclib,
alone and in combination with
identical concentrations of a
PI3K (pictilisib), mTOR
(AZD2014), MEK (trametinib),
ERK (ulixertinib), BRAF
(vemurafenib) or EGFR
(erlotinib) inhibitor for 72
hours. The responses of each
PDX to different treatments
were evaluated by assessing
the reduction of area under the
dose-response curve (AUC) for
the combination treatment
compared to the single-agent
KRAS effector inhibitor
treatment. Top 3 responders
and bottom 3 non-responders
are shown as representative
examples.
Figure 1. PDX tumors were sectioned into uniform tissue
slices at 200 µm thickness and arrayed in 96-well plates. For
each PDX model, tumor tissue slices were treated with
multiple doses of inhibitors for 72 hours. The viabilities of
individual tissue slices were measured with PrestoBlue® and
fluorescence readings were normalized to non-treatment
controls.
Figure 6. PATX179 model (KRAS G12V) was used for an in
vivo experiment in which PDX-bearing mice (n = 4-5 per
group) were treated with vehicle, lerociclib (50 mg/kg, qd),
ulixertinib (50 mg/kg, bid), or lero + uli combination for 38
days. All drugs were given by oral gavage. Tumor volume
changes (%) were calculated and plotted as mean ± SEM.
Figure 4. Differential gene expression analysis identified gene signatures associated with responses to lerociclib + ulixertinib, and GSEA preranked
identified pathways associated with non-responsive (red) and responsive (blue) PDX models. Gene set membership in top panel, correlation with
AUC (in middle panel, and median-centered log2-expression data in bottom panel. Side panel presents the “pathway ratio” (the log2-ratio of gene
expression for pathways associated with non-responsive vs. responsive PDX models) and the measured AUC ratios for non-responsive (brown) and
responsive (purple) PDX models.
Ex Vivo Tissue Slice Assay (LTSA)
Gene Signatures associated with tumor responses to Lerociclib + Ulixertinib treatmentREACTOME_SRP_DEPENDENT_COTRANSLATIONAL_PROTEIN_TARGETING_TO_MEMBRANE
REACTOME_PEPTIDE_CHAIN_ELONGATION
KEGG_RIBOSOME
REACTOME_INFLUENZA_VIRAL_RNA_TRANSCRIPTION_AND_REPLICATION
KEGG_SYSTEMIC_LUPUS_ERYTHEMATOSUS R NR
REACTOME_RNA_POL_I_PROMOTER_OPENING
REACTOME_RNA_POL_I_TRANSCRIPTION R NR
REACTOME_INTEGRIN_ALPHAIIB_BETA3_SIGNALING
Correlation with AUC
PATX179
PATX137
PATX110
PATX147
PATX122
PATX66
PATX69
PATX70
PATX153
PATX43
PATX102
PATX124
PATX53
PATX39
PATX126
PATX55
PATX204
PATX136
PATX118
PATX148
PATX155
PATX142
SHC
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WF
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DH
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T1H
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BH
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PO
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OLR
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DG
TF2
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24
D1
RP
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SRP
RB
SSR
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PN
1SP
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P9
SRP
68
SRP
14
SEC
11
ASE
C6
1B
SEC
61
A1
SRP
72
SEC
11
CR
PS1
4R
PL2
7R
PS7
RP
S18
FAU
RP
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AR
PL2
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RP
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PL2
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Pat
hw
ay R
atio
AU
C
Figure 3. Heat map plotting the AUC ratio of
combination treatment compared to single
agent KRAS effector to illustrate the intensity
and frequency of response enhancements
across each drug combination.
Combinatorial drug treatment enhances the antitumor effects of Lerociclib
Responders Non-responders
Gene signature enrichments associated with response
or resistance to Lerociclib-based combinations
Figure 5. Pathway analysis with GSEA preranked identified
enriched pathways associated with response or non-response of
PDXs to drug combinations.