Immune checkpoint inhibitors in lung cancer: Lights and shadows in Second Line

Mauro Zukin MD, PhD

Américas Oncologia

Potenciais conflitos de interesseCategorias Patrocinadores

Apoio em participação de eventos de cunho científico

Roche, Astra Zeneca, MSD,BMS,Pfizer

Investigador de ensaios clínicos patrocinados

Roche, Astra Zeneca, MSD,BMS, Pfizer, Astellas

Aulas e apresentações Roche, Astra Zeneca,MSD,Pfizer, BMS

Consultorias científicas Roche, Astra Zeneca, MSD,Boehringer-Ingelheim, Pfizer,Lilly

Imune Checkpoint LIGHTS

Focus on PD1/PDL1

IMMUNE

DESERT

Three immune phenotypes point to interruption of specific steps of the cancer-immunity cycle

• Adapted from Chen and Mellman. Immunity 2013; Chen and Mellman. Nature 2017; Kim and Chen. Ann Oncol 2016

INFLAMED

IMMUNE

EXCLUDED

Each phenotype describes the level of T-cell presence and activity within the tumour

microenvironment and is associated to specific immune-escape mechanisms

Non-inflamed tumours

with little or no CD8+

T-cell infiltration

Non-inflamed tumours

with presence of CD8+

T cells that reside

solely in the periphery

Presence of intra-

tumoural CD8+

T-cell infiltrate

Inflamed phenotype

• 1. Spranger, et al. 2013; 2. Tumeh, et al. 2014; 3. Herbst, et al. 2014; 4. Fehrenbacher, et al, 2016; 5. Rosenberg, et al. 2016; 6. McDermott, et al, 2016; 7. Chen & Mellman, 2017; 8. Kim & Chen 2016. Cancer-immunity cycle adapted from Chen & Mellman 2013.

CD8 IHC

Characterised by an abundance of CD8+ T cells within the tumour

In this tumours there is an arrested pre-existing anti-tumour immune response

Associated to escape mechanisms that impair T-cell-mediated recognition and

killing of cancer cells

Escape due to reduced recognition by immune cells

(e.g. down-regulation, loss or alteration of the MHC-I protein)

6

Escape due to reduced effector T-cell function

(e.g. additive checkpoints such as LAG-3, TIGIT or TIM-3; or immunosuppressive cells such as

tumor-associated macrophages, or Tregs).

7

Inflamed phenotype Likely due to a defect in steps 6–7 of the cancer-immunity cycle8

Immune desert phenotype

• 1. Gajewski, et al. 2013; 2. Herbst, et al. 2014; 3. Hedge, et al. 2016; 4. Kim & Chen, 2016; 5. Chen & Mellman, 2017.

• Cancer-immunity cycle adapted from Chen & Mellman, 2013.

Escape due to suboptimal T-cell activation

(e.g. lack of costimulatory interactions between DCs and T-cells, such as OX40 or 4-1BB, limited production of IL-2

or overexpression of CTLA-4)

3

Escape due to reduced DC maturation

(e.g. numerous cancer-derived soluble factors, or

suppressive immune cells)

2

Escape due to poor tumour immunogenicity

(e.g. reduced tumour mutational load,

low MHC-I)

1

Non-inflamed phenotype Likely due to a defect in steps 1–3 of the cancer-immunity cycle4

Characterised by a lack of CD8+ T cells in the tumour parenchyma or

stroma

These tumors are likely to have a defect in the early stages of the cancer immunity cycle

(steps 1-3)

Associated to immune escape mechanisms that impair T-cell

generation

CD8 IHC

Immune excluded phenotype

• 1. Salmon, et al. 2012; 2. Herbst, et al. 2014; 3. Joyce & Fearon, 2015; 4. Hedge et al, 2016; 5. Kim & Chen, 2016; 6. Chen & Mellman, 2017.

• Cancer-immunity cycle adapted from Chen & Mellman, 2013.

Characterised by an abundance of CD8+ T cells that reside solely in the periphery

of the tumour

In these tumors the first stages of the cycle are successful; however active escape mechanisms

prevent T-cells entering the tumor (step 4-5)

Associated to immune escape mechanisms that impair T-cell

trafficking and infiltration

Escape due to impaired T-cell trafficking5

(e.g. increased levels of VEGF)

4

5

Non-inflamed phenotype Likely due to a defect in steps 4–5 of the cancer-immunity cycle5

Escape due to stroma-dependent exclusion 5

(extracellular matrix produced by cancer associated fibroblasts or CXCL12)

CD8 IHC

Each immune phenotype requires specific, essential T-cell activity to reinitiate the antitumour immune response

• Chen and Mellman. Immunity 2013; Hegde, et al. Clin Cancer Res 2016; Kim and Chen. Ann Oncol 2016; Chen and Mellman. Nature 2017

INFLAMED

KILLtumour

IMMUNE EXCLUDED

INFILTRATEtumour

Essential T-cell activity required

IMMUNE DESERT

GENERATEactive, tumour-directed T cells

What are the data, 2nd Line

OAK, a randomized phase III study comparingatezolizumab with docetaxel in 2L/3L NSCLC

Atezolizumab – All histologies , no PDL1 selection

Atezolizumab based on PDL1 +

Pembrolizumab – Keynote 010 All histologies, PDL1 cut off > 1%

OS, PD-L1 TPS ≥50% Stratum

Analysis cut-off date: September 30, 2015.

Treatment ArmMedian

(95% CI), moHRa

(95% CI) P

Pembro 2 mg/kg 14.9 (10.4-NR) 0.54 (0.38-0.77)

0.0002

Pembro 10 mg/kg 17.3 (11.8-NR) 0.50 (0.36-0.70)

<0.0001

Docetaxel 8.2 (6.4-10.7) — —

aComparison of pembrolizumab vs docetaxel.

0 5 10 15 20 250

10

20

30

40

50

60

70

80

90

100

Time, months

Overa

l lS

urv

ival,

%

139

151

152

110

115

90

51

60

38

20

25

19

3

1

1

0

0

0

2 vs 10 mg/kg: HR 1.12, 95% CI 0.77-1.62

Nivolumab –Checkmate 017/056no PDL1 selection

OS (3 years’ minimum follow-up)

19CI = confidence interval; HR = hazard ratio

292

194

148

112

82 58 49 39 7 0

290

195

112

67 46 35 26 16 1 0

135

86 57 38 31 26 21 16 8 0

137

69 33 17 11 10 8 7 3 0

CheckMate 057 (non-SQ NSCLC)CheckMate 017 (SQ NSCLC)

No. of patients at risk

Nivolumab

Docetaxel

No. of patients at risk

Nivolumab

Docetaxel

0 6 12 18 24 30 36 42 48 54

Δ10%

Nivolumab (n = 135)

Docetaxel (n = 137)

1-y OS = 42%

2-y OS = 23%

3-y OS = 16%1-y OS = 24%

2-y OS = 8%3-y OS = 6%

HR (95% CI): 0.62 (0.48, 0.80)

100

80

60

40

20

0

OS

(%)

Months

Δ18%

Δ15%

0 6 12 18 24 30 36 42 48 54

Months

1-y OS = 51%

2-y OS = 29%

3-y OS = 18%

1-y OS = 39%

2-y OS = 16%

3-y OS = 9%

Nivolumab (n = 292)

Docetaxel (n = 290)

HR (95% CI): 0.73 (0.62, 0.88)

100

80

60

40

20

0O

S (%

)

Δ12%

Δ13%

Δ9%

CheckMate 057

N Engl J Med 2015;373:1627-39.

Immune checkpoints LIGHTS

Conclusions in second line

Both PD- 1 and PD-L1 treatment show a consistent increase in OS compared to docetaxel

Immune checkpoints SHADOWSPFS curve in non-sq NSCLC

PD-1/PDL1 is targeted treatment

How to bring light into the shadow • Patient selection !

• PD-L1 expression enriches, but far from perfect

• PD-1 inhibitors have substantial activity in NSCLC, immunotherapy has completely changed the landscape of NSCLC therapy

• PD-1 inhibitors do not work in the majority of patients

• When they do, it is unclear how long we need to treat

• Efforts to improve this

Improvement of biomarkers

Identification of clinical populations more and less likely to benefit

Combining immunotherapy with other treatments

• Combination IO

• Combination with chemotherapy

• Combination with Chemotherapy + VEGFi