Immuno-Oncology Biomarkers:Progress UpdateJosep M. Piulats, MD, PhDDepartment of Medical Oncology, Institut Català d’Oncologia–IDIBELL, Barcelona, Spain

IOES18NP02971-02

Date of preparation: October 2018

Advisory board Astellas, BeiGene, Bristol-Myers Squibb, Clovis, Janssen, Merck KGaA/EMD Serono, Merck, Sharp & Dohme, Novartis, Roche and VCN Biosciences

Research funding

AstraZeneca, Bristol-Myers Squibb, Incyte, Merck KGaA/EMD Serono, Merck, Sharp & Dohme and Pfizer

Clinical trial participation (principal investigator)

Astellas, AstraZeneca, BeiGene, Bristol-Myers Squibb, Clovis, Immunocore, Janssen, Lilly and Merck, Sharp & Dohme

Disclosures

• The discovery of RELIABLE biomarkers to predict the efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research

• No efficient study designs to identify promising candidate biomarkers have been established

• This has led to a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated

• Many anticancer drugs are developed below their potential, due to failure to identify predictive biomarkers

– Unnecessary toxicities and costs

– Inability to identify the specific patient populationin which they are active

Biomarkers in Melanoma: BRAF Mutations—Are We There in I-O?1

EGF = epidermal growth factor; EGFR = EGF receptor; FGF = fibroblast growth factor; FGFR = FGF receptor; HRG = heregulin; I-O = immuno-oncology; PDGF = platelet-derived growth factor;

PDGFR = PDGF receptor.

1. Perez-Gracia JL et al. Cancer Treat Rev. 2017;53:79-97. 2. Pratilas CA et al. Clin Cancer Res. 2010;16:3329-3334.

Adapted from Pratilas CA et al. 2010.2

Images provided by JM Piulats.

HLAI = human leukocyte antigen-I; TCR = T-cell receptor.

Images provided by JM Piulats.

HLAI = human leukocyte antigen-I; PD-1 = programmed death 1; TCR = T-cell receptor.

Images provided by JM Piulats.

HLAI = human leukocyte antigen-I; IFN-γ = interferon gamma; PD-1 = programmed death 1; TCR = T-cell receptor.

Images provided by JM Piulats.

HLAI = human leukocyte antigen-I; IFN-γ = interferon gamma; PD-1 = programmed death 1; PD-L1 = programmed death ligand 1; TCR = T-cell receptor.

Images provided by JM Piulats.

HLAI = human leukocyte antigen-I; IFN-γ = interferon gamma; PD-1 = programmed death 1; PD-L1 = programmed death ligand 1; TCR = T-cell receptor.

Images provided by JM Piulats.

Primary Tumors Metastasis

AIS = adjusted inflammation score; TIL = tumor-infiltrating lymphocyte.

Adapted from Taube JM et al. Sci Transl Med. 2012;4:127ra37.

Fig 1 in Taube

source file

Colocalization of Inflammatory Response With PD-L1 Expression in Human Melanocytic Lesions Supports an Adaptive Resistance Mechanism of Immune Escape

Tx = treatment.

Adapted from Tumeh PC et al. Nature. 2014;515:568-571.

PD-1 Blockade Induces Responses by InhibitingAdaptive Immune Resistance

Spatiotemporal Dynamics of CD8+ Releasing the PD-1 Checkpoint Led to:

2. Intratumoral infiltration

3. Increased effector function

1. T-cell proliferation

Adapted from Tumeh PC et al. Nature. 2014;515:568-571.

PD-1 Blockade Induces Responses by InhibitingAdaptive Immune Resistance

TCR Clonality:

Low Diversity

High Clonality

High Diversity

Low Clonality

Images provided by JM Piulats.

Spontaneous

Treatment Induced

Images provided by JM Piulats.

Spontaneous

Treatment Induced

Images provided by JM Piulats.

Spontaneous

Treatment Induced

Images provided by JM Piulats.

Biomarkers in I-O

Neoantigens

Antigen presentation machinery

IFN-𝛄 signatures

IFN-𝛄–related proteins

Immune-staining cell populations

Adapted from Clancy S et al. Nature Education. 2008;1:101.

ALL = acute lymphoblastic leukemia; CLL = chronic lymphocytic leukemia; DLBCL = diffuse large B-cell lymphoma.

Adapted from Lawrence MS et al. Nature 2013;499:214-218.

Somatic Mutation Frequencies Observed in Exomes From 3083 Tumor-normal Pairs

MMRd = mismatch repair–deficient; MMRp = mismatch repair–proficient; NSCLC = non-small cell lung cancer.

Adapted from Yarchoan M et al. N Engl J Med. 2017;377:2500-2501.

Correlation between Tumor Mutational Burden and Objective Response Rate with Anti–PD-1 or Anti–PD- L1 Therapy

Seq. = sequence.

Adapted from Snyder A at al. N Engl J Med. 2014;371:2189-2199.

Defects in DNA-repairing Genes as a Source for DNA Mutations: Do They Predict Response to Checkpoint Inhibitors?

DCB = durable clinical benefit; NDB = no durable benefit; NR = not reached; PD = progressive disease; PFS = progression-free survival; PR = partial response; SD = stable disease; V = validation.

Adapted from Rizvi NA et al. Science. 2015;348:124-128.

Defects in DNA-repairing Genes as a Source for DNA Mutations: Do They Predict Response to Checkpoint Inhibitors?

HR = hazard ratio; ITH = intratumor heterogeneity.

Adapted from McGranahan N et al. Science. 2016;35:1463-1469.

Defects in DNA-repairing Genes as a Source for DNA Mutations: Do They Predict Response to Checkpoint Inhibitors?

PD-1 Blockade in Tumors With Mismatch-Repair Deficiency

Adapted from Le DT et al. N Engl J Med. 2015;372:2509-2520.

Defects in DNA-repairing Genes as a Source for DNA Mutations: Do They Predict Response to Checkpoint Inhibitors?

INDEL = insertion and deletion; nsSNV = nonsynonymous single nucleotide variant; Pt = patient; WT = wild type.

Adapted from Hugo W et al. Cell. 2016;165:35-44.

Defects in DNA-repairing Genes as a Source for DNA Mutations: Do They Predict Response to Checkpoint Inhibitors?

Small INDELs

Frameshift Mutations:

Not All Genetic Alterations Are the Same…

Image provided by JM Piulats.

Not All Genetic Alterations Are the Same…

Adapted from Turajlic S et al. Lancet Oncol. 2017;18:1009-1021.

Not All Genetic Alterations Are the Same…

Adapted from Davoli T et al. Science 2017;355:eaaf839.

LOH = loss of heterozygosity; MHC = major histocompatibility complex.

Adapted from Chowell D et al. Science. 2018;359:582-587.

Patient HLA Class I Genotype Influences Cancer Response to Checkpoint Blockade Immunotherapy

Adapted from Hugo W et al. Cell. 2016;165:35-44.

Genomic and Transcriptomic Features of Response to Anti–PD-1 Therapy in Metastatic Melanoma

1. Non responding tumors expressed higher:

– Mesenchymal transition genes (AXL, ROR2, WNT5A, LOXL2, TWIST2, TAGLN, FAP).

– Immunosuppressive genes (IL10, VEGFA, VEGFC).

– Monocyte/macrophage chemotactic genes (CCL2, CCL7, CCL8, CCL13)

– Genes associated with wound healing and angiogenesis.

2. CDH1 was down-regulated in non-responders.

3. Genes with putative roles in modulating immune-checkpoint sensitivity were not differentially expressed.

4. GZMA, PRF1, PDCD1LG2, and CTLA-4 were expressed higher in patients who derived benefit from ipilimumab.

5. GZMA, PRF1, PDCD1LG2, CTLA-4, CD8A/B, PD-L1, LAG3, and INFG did not present higher expression in responders.

6. Expression levels of HLA class I genes trended higher among responding tumors.

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Adapted from Ayers M et al. J Clin Invest. 2017;127:2930-2940.

IFN-g–related mRNA Profile Predicts Clinical Response to Anti–PD-1 Blockade

Adapted from Ayers M et al. J Clin Invest. 127;2017:2930-2940.

IFN-g–related mRNA Profile Predicts Clinical Response to Anti–PD-1 Blockade

GEP = gene expression profile; TMB = tumor mutational burden.

Adapted from Cristescu R et al. Science. 2018;362:eaar3593.

TMB and GEP were independently

predictive of response and

demonstrated low correlation,

suggesting that they capture

distinct features of neoantigenicity

and T-cell activation

Pan-Tumor Genomic Biomarkers for PD-1 Checkpoint–Blockade-based Immunotherapy

PF

S

Time to progression (days)

MSI-h = microsatellite instability high; MSS = microsatellite stable; SCC = small cell carcinoma; TNBC = triple-negative breast cancer.

Adapted from Cristescu R et al. Science. 2018;362:eaar3593.

Pan-Tumor Genomic Biomarkers for PD-1 Checkpoint–Blockade-based Immunotherapy

PF

S

Time to progression (days)

PD-L1 < 1%

PD-L1 > 1%

aPD-L1 positive: ≥ 5% tumor cell surface staining. PD-L1 negative: < 5% tumor cell surface staining. Based on August 5 2014 database lock.

CI = confidence interval; IPI = ipilimumab; NIVO = Nivolumab; NR=not reached; OS = overall survival.

1. Robert C et al. N Engl J Med. 2015;372:320-330. 2. Wolchok JD et al. N Engl J Med. 2017;367:1345-1356.

Just One Slide About PD-L1 Staining…

Improved OS irrespective of PD-L1 status100

90

80

70

60

0

50

40

30

20

10

0 3 6 9 12 15 18Months

Nivolumab PD-L1+

Dacarbazine PD-L1+

Nivolumab PD-L1-

Dacarbazine PD-L1-

Patients at Risk

Dacarbazine PD-L1-

Nivolumab PD-L1-

Dacarbazine PD-L1+

Nivolumab PD-L1+

74

128

74

126

69

108

64

107

56

88

44

78

39

63

30

52

18

26

11

11

1

7

1

2

0

0

0

0

Pati

en

ts S

urv

ivin

g (

%)

OS by PD-L1 Statusa

Patients who died,

n/NMedian OS mo (95% CI)

1-Yr OS% (95% CI)

Nivolumab PD-L1+ 11/74 NR 82.1 (69.6–89.8)

Nivolumab PD-L1- 37/128 NR 67.8 (58.3–75.7)

Dacarbazine PD-L1+ 29/74 12.4 (9.2–NR) 52.7 (37.7–65.7)

Dacarbazine PD-L1- 64/126 10.2 (7.6–11.8) 37.4 (26.4–48.3)

Adapted from Robert C et al. 2015.1

Adapted from Wolchok JD et al. 2015.2

Lymphocytes in the Tumor

Lymphocytes in the Tumor

Primary Tumors Metastasis

AIS = adjusted inflammation score; TIL = tumor-infiltrating lymphocyte.

Adapted from Taube JM et al. Sci Transl Med. 2012;4:127ra37.

Fig 1 in Taube

source file

Colocalization of Inflammatory Response With PD-L1 Expression in Human Melanocytic Lesions Supports an Adaptive Resistance Mechanism of Immune Escape

AIS = adjusted inflammation score; TIL = tumor-infiltrating lymphocyte.

Adapted from DB Johnson et al. Clin Cancer Res. 2018;24:5250-5260.

Quantitative Spatial Profiling of PD-1/PD-L1 Interaction and HLA-DR/IDO-1 Predicts Improved Outcomes of Anti-PD-1 Therapies in Metastatic Melanoma

AIS = adjusted inflammation score; TIL = tumor-infiltrating lymphocyte.

Adapted from DB Johnson et al. Clin Cancer Res. 2018;24:5250-5260.

Quantitative Spatial Profiling of PD-1/PD-L1 Interaction and HLA-DR/IDO-1 Predicts Improved Outcomes of Anti-PD-1 Therapies in Metastatic Melanoma

AIS = adjusted inflammation score; TIL = tumor-infiltrating lymphocyte.

Adapted from DB Johnson et al. Clin Cancer Res. 2018;24:5250-5260.

Quantitative Spatial Profiling of PD-1/PD-L1 Interaction and HLA-DR/IDO-1 Predicts Improved Outcomes of Anti-PD-1 Therapies in Metastatic Melanoma

AIS = adjusted inflammation score; TIL = tumor-infiltrating lymphocyte.

Adapted from M Sade-Feldman et al. Cell. 2018;175:998-1013.

Defining T Cell states Associated with Response to Checkpoint Immunotherapy in Melanoma

Adapted from Zitvogel L et al. Science. 2018;359:1366-1370.

…. And Last: The Microbiome

Gut Microbiome Modulates Response to

PD-1–based Immunotherapy in Melanoma PatientsGut Microbiome Influences Efficacy of

PD-1–based Immunotherapy Against Epithelial Tumors

1. Gopalakrishnan V et al. Science. 2018;359:97-103. 2. Routy B et al. Science. 2018;359:91-97.

The Microbiome and PD-1–based Immunotherapy

Adapted from Rouly B et al. 2018.2Adapted from Gopalakrishnan V et al. 2018.1

Conclusions:

• The perfect biomarker does not exist.

• Objective for a biomarker in I-O: Select patients that will benefit from anti-PD1 alone.

• We can divide biomarkers in:

– Genetic: Tumor mutation burden (TMB). Still margin for improvement…

– INF-g related:

• These biomarkers seems to work better when we combine:

- TMB + LOH loss for HLA locus.

- TMB + INF-g related biomarker.

• Importance of exploring more microbiota as single biomarker or associated with other.

Gene signatures.

Single gene (PD-1).

Imaging (new tools ).