Immunotherapy in Cancer: How It All Began

Drew Pardoll MD, PhD Director, Bloomberg-Kimmel Institute

Johns Hopkins School of Medicine

Immunotherapy: History, Present Status & Future

“Ten years fromtoday, >50% of patients with inoperable cancer will be receiving some form of immunotherapy”- Drew Pardoll

January, WSJ, 2014

1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2015

Discovery of antibodies/magic bullet theory

Monoclonalantibodies

Elucidation oftumor-associated

antigens

Elucidation ofimmune checkpoints

Elucidation of howT cells recognize antigen

Coley’s toxins

Approval of IL-2 for melanoma

TIL formelanoma

αCTLA-4 approvedfor melanoma

αPD-1 formelanoma,renal, lung

αPD-1 in10 morecancers,TVEC formelanomaCD19 bitesfor B-ALL

CAR Ts

Advances in Cancer Immunology & Immunotherapy

ClinicalImmunotherapy

Milestones

Basic Immunology/Cancer

Immunology TIL, tumor-infiltrating lymphocytes

Phan GQ, et al. Proc Natl Acad Sci U S A. 2003;100(14):8372-8377. Attia P, et al. J Clin Oncol. 2005;23(25):6043-6053. Yang JC, et al. J Immunother. 2007;30(8):825-830.

Immune Checkpoint Blockade: Anti-CTLA-4• 10 % objective response rate (mel and RCC)• 23%-33% grade 3/4 autoimmune toxicities• 1st approved checkpoint inhibitor but ONLY melanoma as single agent

PRE-RX POST-RX

Colitis

Hepatitis

Dermatitis

Activation(cytokines, lysis, prolif.,

migration)

Role of CTLA-4 vs PD-1 in Suppressing Antitumor Immunity

Tumor

PD-1

(-)(-) (-)

Inhibition

PD-1 expressedTraffic to tumor

APC T cellB7.1/2 CD28

TCR Signal 1MHC-Ag

Tumoror Vaccine

B7.1/2 CTLA-4

+

-

Lung (NSC, SC) 155,000 20% 1.5 = 46,500Mesothelioma 5000 30% 1.5* = 2250Breast (TN) 12,000 20% 1.5* = 3600Bladder 16,000 30% 1.5* = 7200Melanoma 9000 40% 2.5 = 9000Kidney 14,000 25% 1.5 = 5250Liver 25,000 20% 1.5* = 7500Gastric 11,000 25% 1.5* = 4125Esophageal 15,000 25% 1.5* = 5625Head & Neck 9000 25% 1.5* = 3375Ovarian 14,000 15% 1.5* = 3150Merkel Cell 1000 70% 1.5* = 1050MSI (multiple) 15,000 65% 3.0* = 29,250

127,875 pt yrs

Mutation-targeted drugs #Annual cases %mutated Resp. rate Durability (yrs)NSCLC (EGFR+ALK+ROS1+BRAF): 128,000 15% 60% .6 = 6396 Melanoma (BRAF+cKIT): 9000 60% 60% .6 = 1620Pap. thyroid ca/CRC (BRAF): 3500 60% 50% .6 = 630GIST (cKIT): 1500 60% 70% 1 = 525Basal cell ca (Hh) 2000 60% 45% 1.6 = 1440

10,611 pt yrs

Anti-PD-1/L1 #Annual cases Resp. Rate Durability (yrs)

Patient-Years of Tumor Remission for Solid Cancers in US: PD-1 Blockade vs Mutant Oncogene-Targeted Drugs

* Estimated as DOR not available yet

• >50% of cancer patients will receive immunotherapy by 2025

• >$80B market by 2025• Chemotherapy market will decrease

>50% by 2025• Oncogene-targeted therapy will become

a “primer” for immunotherapy

Conservative Predictions for theFuture of Cancer Immunotherapy

Long-Term Survival of Patients With Melanoma Receiving Immune Checkpoint Blocking Drugs

0 1 2 3 4 5 6 7 8 9 10

100

90

80

70

60

0

50

40

30

20

10Ove

rall

Surv

ival

, %

Years

IPI (Pooled analysis – mixture of 1st & 2nd line)NIVO Monotherapy (Second-Fourth line)NIVO Monotherapy (First line)

At 5 yrs,50% willhave died

Duration of Response and Overall SurvivalLung Cancer

NSCLC Respondersa,b by Histology

Time, Week0 8 16 24 32 40 48 56 64 72 80 88 96 104 112 120 128 136 144 152 160

Vertical line at 96 weeks = maximum duration of continuous nivolumab therapy

a Responses were assessed by modified RECIST v1.0bAll efficacy analyses based on data collected as of September 2013

Squa

mou

sN

onsq

uam

ous

Duration of response up to discontinuation of therapyOngoing responseTime to responseResponse duration following discontinuation of therapy

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Months Since Initiation of Treatment129 111 82 66 48 35 31 28 20 9 4 3 3 3 2 1 1 1 0 0

Subjects at RiskTotal

All Treated Subjects With NSCLC

Died/Treated Median (95% CI)94/129 9.90 (7.80,12.40)

Prop

ortio

n Su

rviv

al Median OS: 9.9 Months (7.8, 12.4)

1-Year OS Rate 42% (48 pts at risk)

2-Year OS Rate 24% (20 pts at risk)

At 4 yr,85% willhave died

Brahmer JR, et al. J Clin Oncol. 2014;32(5_Suppl): Abstract 8112. Brahmer JR, et al. J Thorac Oncol. 2014;9(4 Suppl1): Abstract 96PD.

TUMOROncogenicpathway (AKT)or geneamplification

T CellTCR

PD-1

MHC-peptide

PD-L1

Constitutive tumor signalinginduces PD-L1 on tumor cells

Innate (Tumor-Cell Intrinsic) Resistance

TUMOR

STATs

TUMOR T Cell T Cell

IFN-g

T cell–induced PD-L1 upregulationAdaptive Resistance

STATsTumor-infiltrating leukocyte

PD-1

PD-L1

Topalian SL, et al. Cancer Cell. 2015;27(4):450-461.

Implication: The immune surveillance hypothesis was half right – patients DO have an extant repertoire of antitumor T cells

**

**

**

*

**

*

Tumor Tumor-specific T cell

Tumor-specific T cell

Genetic Mutations In Cancer Encode Altered Proteins- Some can be “tumor-specific antigens” – the biochemical signature

that the immune system uses to recognize the tumor as “foreign”

*

*

****

**

Many mutations Many antigens Stronger immune response

Mutational Heterogeneity in Cancer: Altered Proteins Contain Neoepitopes for Immune Recognition

Does mutational load correlate with responsiveness to immune checkpoint blockade?

*Triplenegative

Lawrence MS, et al. Nature. 2013;499(7457)214-218.

Colorectal Cancers Are Generally Unresponsive to PD-1 Blockade, but the MSI-High Subset Has a High

Mutational Load

Microsatellite instability (MSI): genetic hypermutabilityresulting from impaired DNA mismatch repair, present in ~15% colon cancers, 5%-20% of multiple other tumor types

Lawrence MS, et al. Nature. 2013;499(7457)214-218.

-1 0 0

-5 0

0

5 0

1 0 0M M R -p ro fic ie n t C R C

M M R -d e fic ie n t C R C

M M R -d e fic ie n t n o n -C R C

% C

ha

ng

e f

rom

Ba

se

lin

e S

LD

Objective ResponsesMMR-Deficient CRC

(MSI) MMR-Proficient CRC

(MSS)

MMR-Deficient Non-CRC

(MSI) N 13 25 10Objective Response Rate 62% 0% 60%

Disease Control Rate 92% 16% 70%

Le DT, et al. J Clin Oncol. 2015;33(suppl): Abstract LBA100.

*

*

*

Tumor

Tumor-specific T cell

Even in Tumors With a Lower # of Mutations, One or Two Will Likely Produce a Tumor Antigen

More Than 90% of Patients Possess Tumor-Specific T Cells

Much evidence for T-cell responses against shared tumor-associated antigens – ie, self antigens upregulated in tumors (cancer-testes Ag), but their role in antitumor immunity remains to be determined

Viral antigens in virus-induced cancers are the other type of

neoantigen

EBV (Hodgkin, Burkitt, NPC)HPV (cervical, vulvar, anal, H&N)

MCPyV (Merkel cell cancer)HBV, HCV (liver cancer)

Overview: Merkel Cell Carcinoma• ~ 2,000 cases/year in the US• UV exposure, age >50, immune suppression• Merkel cell polyomavirus present in 80% of

cases

Feng H, et al. Science. 2008;319(5866):1096-1100.

> 40% of MCC patients develop distant disease...

Goh G, et al. Oncotarget. 2015;7(3):3403-3415.

Virus-positive vs negative

MCC: at the extremes of mutational frequency

compared to TCGA data for other cancers

Virus Positive Virus Negative

UV mutations

MCC antigens: Virus-positive tumors have a low mutational burden, but express viral

oncoproteins that are strong immune stimulants (ORR = 62%) Virus-negative tumors have a very high carcinogen-induced

mutational burden (UV light) (ORR = 44%) Nghiem PT, et al. N Engl J Med. 2016;374(26):2542-2552.

Why Don’t More Patients Respond to Anti-PD-1?

How do we capture the remaining 80%-90%?

1) Multiple checkpoints on antitumor T cellsSolution – multicheckpoint blockade (>500 trials)

EGFR, Stat3Raf/MEK

Tumor

DendriticCell

Treg

Tumor-specific

CTL

MΦ/MDSC

PD-L1

PD-L1

Tumor Antigens

Antitumor Cytotoxic T Cell Responses Against Tumors Are Suppressed by Multiple Mechanisms

IL10,TGFβ

IL-35Neuritin

IDOArginase

PD-1LAG-3

Tim3TIGIT

T helperCell

Foxp3

Tbet

HLANeuropilinCTLA4

TIGITGITR

“Help” topromote CTL

1) Multiple checkpoints on antitumor T cellsSolution – multicheckpoint blockade (>500 combotrials, αPD-1 + αCTLA-4 promising, but high toxicity)

2) Suppressive cells in the tumor microenvironment:a) Treg, b) myeloid-derived suppresor cells/MΦSolution – block receptors that promote these cells or

block suppressive molecules they produce3) Endogenous antitumor T-cell response too weak

Solution – Activate the T cells the patient has: a) vaccinesb) intra-tumor injection (endogenous vaccine)c) targeted therapy (BRAF, EGFR, MEK in clinic)

4) Chimeric antigen receptor and TCR-engineered ACT

Why Don’t More Patients Respond to Anti-PD-1?

How do we capture the remaining 80%-90%?

Considerations for Predictive Biomarker Use in Clinical Development of Immunotherapies• No obvious clean selection biomarker such as

oncogene mutation. MSI best current biomarker, PD-L1 second best – 4 PD-L1 tests approved. CD8 infiltrate a possibly simpler biomarker.

• In the absence of a “clean” biomarker, imperfect biomarkers useful in prioritizing (ie, 1st vs 2nd line)

• If biology suggests the target is acting in the tumor microenvironment, the likely biomarker will be in the tumor biopsy

• Retrospective analysis of biomarker expression and its correlation with response are the first step in defining useful biomarkers

Pretreatment Tumor PD-L1 Expression Correlates With Response to Anti-PD-1 Pembrolizumab) in

NSCLC: Individualizing Treatment Strategy

≥ 50% tumor cells PD-L1+- Response rate 45%- Median survival not reached

< 50% tumor cells PD-L1+- Response rate 11%-17%- Median survival 8.8 months

Garon EB, et al. N Engl J Med. 2016;372(21):2018-2028.

Bloomberg~Kimmel Institute for Cancer Immunotherapy at Johns Hopkins

Thanks to patients and collaborating clinical trial centers.