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

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REACTOME_INTEGRIN_ALPHAIIB_BETA3_SIGNALING

Correlation with AUC

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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.