Abstract No. 3469. Presented at the 2020 AACR Virtual Annual Meeting II, June 22–24, 2020

Evaluation of immune phenotypes and gene expression profiles in tumors from patients treated with bintrafusp alfa

George Locke1, Christian Ihling2, Christoph Helwig2, Laureen S. Ojalvo1, Olaf Christensen1, Isabelle Dussault1

1EMD Serono Research & Development Institute, Inc., Billerica, MA, USA; a business of Merck KGaA, Darmstadt, Germany; 2Merck KGaA, Darmstadt, Germany

Poster No. 3290

INTRODUCTION

TGF-β and the immune system• The TGF-β pathway can promote cancer progression and immune

evasion via regulatory effects on immune cells. It is also known to induce angiogenesis, fibrosis, and epithelial–mesenchymal transition (EMT)1-3

• Molecular profiling in mouse tumor models has demonstrated frequent dysregulation of TGF-β signaling and suppression of the T–cell mediated antitumor response in tumor samples4,5

– TGF-β activity in the tumor microenvironment (TME) might attenuate the efficacy of, or even promote resistance to, anticancer therapies, including anti–PD-(L)1 therapies6-8

• Thus, inhibiting TGF-β activity in the TME while simultaneously blocking an additional immunosuppressive cellular mechanism, such as the PD-(L)1 pathway, may provide a novel treatment approach9

• Additionally, different tumor immune phenotypes, each characterized by the level of immune cells infiltrating the tumor area, have been shown to affect responses to different immunotherapy agents across tumor types10,11

Bintrafusp alfa• Bintrafusp alfa is a first-in-class bifunctional fusion protein composed of

the extracellular domain of the TGF-βRII receptor to function as a TGF-β “trap” fused to a human immunoglobulin G1 antibody blocking PD-(L)1 (Figure 1)

– Dual inhibition of TGF-β and PD-(L)1 in the TME by bintrafusp alfa may be more effective than either therapy alone

• Data from two phase 1 studies of bintrafusp alfa (NCT02517398 and NCT02699515) have demonstrated a manageable safety profile and early signs of clinical efficacy in patients with heavily pretreated solid tumors11-16

• Here, we describe the association between response to bintrafusp alfa and immune phenotype in biliary tract cancer (BTC), esophageal adenocarcinoma (EAC), esophageal squamous cell carcinoma (ESCC), gastric cancer (GC), non-small cell lung cancer (NSCLC), squamous cell carcinoma of the head and neck (SCCHN), and triple-negative breast cancer (TNBC) as well as gene expression patterns across the different immune phenotypes

Figure 1. Proposed mechanism of action of bintrafusp alfa

Fibroblast

CAF

Fibrosis and impaireddrug access

EMT (leading to metastasis and resistanceto therapy [including checkpoint inhibition])

Tumor angiogenesis

Tumor cells

PD-L1

Bintrafuspalfa

PD-1

T cell

Suppression of immune response

NK cell

TAMDendritic

cell

CytotoxicT cell

Tumor cellsMesenchymal-like

tumor cell

TGF-β trap moiety sequestersTGF-β to inhibit downstream signaling

Anti–PD-L1 mAb moietyblocks PD-L1 interactions with PD-1

TGF-β*

CAF, cancer-associated fibroblast; NK, natural killer; TAM, tumor-associated macrophage.

*Tumor cells are also a major source of TGF-β in the TME.

METHODS

• NCT02517398 and NCT02699515 are ongoing (but no longer recruiting), phase 1, open-label trials of bintrafusp alfa with multiple expansion cohorts in different tumor types. Patients received bintrafusp alfa 1200 mg every 2 weeks (Q2W) until confirmed progressive disease, unacceptable toxicity, or trial withdrawal

– A subset of patients in the NSCLC cohort (n=40) received bintrafusp alfa 500 mg Q2W

• The primary objectives are best overall response per RECIST 1.1 and safety in the NCT02517398 and NCT02699515 trials, respectively

• Archival tumor samples were used to determine immune phenotype based on available immunohistochemistry data (PD-(L)1 stain and PD-(L)1 negative control) and hematoxylin and eosin staining

• Tumors were categorized into 3 immune phenotypes using an exploratory classification system:15-17

– Inflamed: immune cells in direct physical contact with tumor cells – Immune-excluded: ≥1% of tumor stroma area populated by lymphocytes,

immune cells possibly located in immediate vicinity of tumor cells but not efficiently infiltrating tumor cell clusters, and very infrequent physical contact between lymphocytes and tumor cells

– Immune-desert: <1% of tumor stroma area populated by lymphocytes, no dense immune cell infiltrates, and no contact of immune cells with tumor cells

• A pathologist who was masked to the response data scored the scanned slides and determined the corresponding immune phenotype

• Gene expression analysis was performed using RNA sequencing data as previously described15,16

RESULTSImmune phenotype analysis• Across archival tumor samples from different cohorts of the phase 1

NCT02517398 and NCT02699515 studies, most patients had immune-excluded tumors (163/247; 66.0%)

• The frequency of immune phenotypes varied by tumor type; however, immune-excluded tumors were the most common within each cohort (Figure 2A)

– Inflamed tumors were not or rarely observed in the TNBC (0/30; 0%) and BTC (2/28; 7.1%) cohorts

– Immune-desert tumors were uncommon in the EAC (1/27; 3.7%), ESCC (1/30; 3.3%), and GC (1/30; 3.3%) cohorts

• Responses to bintrafusp alfa determined by an independent review committee were observed primarily in tumors with an immune-excluded (26/44 responders; 59.1%) or inflamed (15/44 responders; 34.1%) phenotype, with different distributions across cohorts (Figure 2B)

– The immune-excluded phenotype was most common in responders with BTC (5/6; 83.3%), EAC (5/6; 83.3%), ESCC (3/3; 100%), and TNBC (2/3; 66.7%)

– The inflamed phenotype was most common in responders with GC (4/5; 80.0%) and SCCHN (3/4; 75.0%)

– Responses in the NSCLC cohort occurred at a similar frequency in both immune-excluded (9/17; 52.9%) and inflamed (7/17; 41.2%) tumors

– Overall, responses rarely occurred in patients with immune-desert tumors (n=1 each in the BTC, NSCLC, and TNBC cohorts)

Figure 2. Distribution of immune phenotype and response to bintrafusp alfa across various heavily pretreated tumors*A. Distribution of immune phenotype across cohorts

TNBC (n=30)

BTC (n=29) 24 32

18 18

25 14

15 114

44 918

19 310

19 11

ESCC (n=30)

NSCLC (n=71)

EAC (n=27)

SCCHN (n=32)

GC (n=30)

0 25 50 75 100Patients, (%)

Inflamed

Immune-excluded

Immune-desert

B. Distribution of responders and nonresponders by immune phenotype across cohorts

TNBC (n=3)

BTC (n=6)

ESCC (n=3)

NSCLC (n=17)

EAC (n=6)

SCCHN (n=4)

GC (n=5)

0 25 50 75 100Patients, (%)

Inflamed

Immune-excluded

Immune-desert

TNBC (n=27)

BTC (n=23)

ESCC (n=27)

NSCLC (n=54)

EAC (n=21)

SCCHN (n=28)

GC (n=25)

0 25 50 75 100Patients, (%)

Inflamed

Immune-excluded

Immune-desert

Responders to bintrafusp alfa

Nonresponders to bintrafusp alfa

5 1

51

3

4 1

9 17

3 1

2 1

19 22

13 17

22 14

14 110

35 811

18 37

17 10

*Patients who were unevaluable for response or immune phenotype were excluded from these figures.

Gene expression analysis• Inflamed tumors demonstrated a higher level of immune genes, such as TNFRSF9, GZMB, and PRF1, compared with immune-excluded or immune-desert tumors (Figure 3A)

– On average, the overall range of gene expression in both immune-excluded and inflamed tumors overlapped and was not distinguishable between the 2 immune phenotypes

• In the ESCC and TNBC cohorts, immune-excluded tumors showed associations with TGF-β signaling (increased expression of ACTA2 in the ESCC cohort and of HMGA2 in the TNBC cohort; Figure 3B); this potential link was less clear in other tumor types (data not shown)

Figure 3. Gene expression analysis across immune phenotypesA. Transcriptomic profiling across immune phenotypes

CCL4

PLEK

GNLY

PRF1

NKG7

GZMB

TNFRSF9

IL2RB

ICOS

SIRPG

SNX20

IL23A

OSM

MMP25

GPR97

Immune phenotypeIndication Indication

BTC

ESCCEAC

GCNSCLCSCCHNTNBC

Immune phenotypeImmune-desertImmune-excludedInflamed

Significant differentialexpression

UpNot significantDown

−4

−2

0

2

4

Inflamed vs othersImmune-excluded vs Inflamed

B. Genetic profiling across immune phenotypes*

5

6

7

8

9

Immune-excluded Inflamed

log 2(T

PM+0

.5)

ACTA2 expression in ESCC

2

4

6

8

10

Immune-desert Immune-excluded

log 2(T

PM+0

.5)

HMGA2 expression in TNBC

TPM- Transcripts per million*No patients with TNBC had an inflamed phenotype; 1 patient with ESCC had an immune-desert phenotype, but did not respond to bintrafusp alfa

CONCLUSIONS

• While the distribution of immune phenotypes varied by tumor type, the immune-excluded phenotype was the most common across cohorts

• Responses to bintrafusp alfa were more common in inflamed tumors in some cohorts (GC and SCCHN) and in immune-excluded tumors in others (BTC, EAC, ESCC, NSCLS, and TNBC). Responses rarely occurred in immune-desert tumors

• In the ESCC and TNBC cohorts, tumors with an immune-excluded phenotype had elevated expression of genes that are known to be upregulated by TGF-ββ signaling (ACTA2 and HMGA2, respectively), potentially highlighting the importance of TGF-ββ biology in these tumor types and this immune phenotype18-20

• Together, these data suggest that the pathological evaluation of immune phenotype and molecular methods are useful in understanding responses to bintrafusp alfa across indications

• A complementary approach to identify biomarkers is likely needed to more precisely characterize the bifunctional mechanism of action of bintrafusp alfa

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ACKNOWLEDGMENTSThe authors thank the patients and their families, investigators, co-investigators, and the study teams at each of the participating centers and at Merck KGaA, Darmstadt, Germany and EMD Serono Research & Development Institute, Inc., Billerica, MA, USA; a business of Merck KGaA. This study was funded by Merck KGaA, and is part of an alliance between Merck KGaA and GlaxoSmithKline. Medical writing support was provided by Spencer Hughes, PhD, of ClinicalThinking, Inc, Hamilton, NJ, USA, which was also funded by Merck KGaA and GlaxoSmithKline in accordance with Good Publication Practice (GPP3) guidelines (http://www.ismpp.org/gpp3)

Correspondence: Isabelle Dussault, isabelle.dussault@emdserono.com

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