Immuno-Oncology Biomarkers: Progress Update...Immuno-Oncology Biomarkers: Progress Update Josep M....

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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.

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

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

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

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

Spontaneous

Treatment Induced

Spontaneous

Treatment Induced

Spontaneous

Treatment Induced

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.

HR = hazard ratio; ITH = intratumor heterogeneity.

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

PD-1 Blockade in Tumors With Mismatch-Repair Deficiency

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

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.

Small INDELs

Frameshift Mutations:

Not All Genetic Alterations Are the Same…

Image provided by JM Piulats.

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

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.

ADD Text

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

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

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

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+

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

Primary Tumors Metastasis

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

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

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 ).

Immuno-Oncology Biomarkers: Progress Update...Immuno-Oncology Biomarkers: Progress Update Josep M....

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