checkpoint inhibitors in urothelial cancer: biomarkers and ... · a rnaseq data. data cutoff: march...

Checkpoint Inhibitors in Urothelial Cancer: Biomarkers and

Treatment Strategies

Daniel P. Petrylak , MD Professor of Medicine and Urology

Director, Genitourinary DART Co-Director, Signal Transduction Program

Smilow Cancer Center Yale University School of medicine

August 12, 2016

Petrylak DP, et al., Atezolizumab (MPDL3280A) in UBC 2

Efficacy Responses to Atezolizumab by PD-L1 IC Subgroup

•  Responses were seen in all IC subgroups, but ORR was enriched with higher PD-L1 status •  Complete responses accounted for nearly half of the observed responses

–  CRs were observed in all PD-L1 subgroups, with the highest rate in IC2/3 patients •  ORRs per immune-modified RECIST were concordant

a Includes 46 patients with missing/unevaluable responses. b CR + PR + SD ≥ 24-wk rate per IRF RECIST v1.1. Treated patients had measurable disease at baseline per investigator-assessed RECIST v1.1. Data cutoff: Mar. 14, 2016.

IC2/3 n = 100

IC1/2/3 n = 207

Alla N = 310

ORR: confirmed IRF RECIST v1.1 (95% CI)

28% (19, 38)

19% (14, 25)

16% (12, 20)

CR rate: confirmed IRF RECIST v1.1 (95% CI)

15% (9, 24)

9% (6, 14)

7% (4, 10)

IC1 n = 107

IC0 n = 103

11% (6, 19)

9% (4, 16)

4% (1, 9)

2% (0, 7)

2

Dreicer R, et al. IMvigor210: Atezolizumab in platinum-treated mUC. ASCO 2016


•  Longer OS observed in patients with higher PD-L1 IC status •  12-mo OS compares favorably with historic estimates of ≈ 20%1

•  NE, not estimable. a 1 prior line of therapy for mUC and no (neo)adjuvant therapy. Data

cutoff: Mar. 14, 2016. 1. Agarwal Clin Genitourin Cancer 2014.

3

Median follow-up (range): All pts: 17.5 mo (0.2 to 21.1+ mo) 2L only: 17.3 mo (0.5 to 21.1+ mo)

Ove

rall

Sur

viva

l

100

80

60

40

20

0

Time, months 6 8 10 2 4 0 12 14 16 18 20

▮ All Patients + Censored Subgroup

12-mo OS (95% CI)

IC2/3 IC0/1 All All pts (N = 310)

50% (40, 60)

31% (24, 37)

37% (31, 42)

2L only (n = 120)

61% (44, 77)

29% (19, 39)

38% (29, 47)

Subgroup

Median OS (95% CI)

IC2/3 IC0/1 All All pts (N = 310)

11.9 mo (9.0, 17.9)

6.7 mo (5.4, 8.0)

7.9 mo (6.7, 9.3)

2L only (n = 120)

NE (10.9, NE)

7.1 mo (5.0, 9.2)

9.0 mo (7.2, 11.3)

Efficacy Overall Survival

# at Risk: All pts: 310 265 203 176 146 126 110 97 82 35 5

2L only: 120 101 83 72 61 54 44 34 29 11 2

Dreicer R, et al. IMvigor210: Atezolizumab in platinum-treated mUC. ASCO 2016

All Pts and 2L only

▮ All Patients ▮ 2L only + Censored

Control Targeted therapies Immune checkpoint blockade Combinations/sequencing/biomarker selection

Surv

ival

Time Su

rviv

al

Time

Where we are now

Salvati M, 3rd Intl Symp in Lung Ca, 2014; Ribas A, WCM, 2013; Ribas A, et al. Clin Cancer Res 2012; Drake CG. Ann Oncol 2012 Friends Brookings Conference 2013

Could Biopsies and Biomarkers help?

Where we want to be

T-‐cells •  How many? •  What type? •  Recognize tumor an:gens? •  Breadth of an:gen recogni:on (one, a

few, many) •  Affinity of TCR for pep:de-‐MHC complex •  Func:onal state •  Differen:ated state •  Expression of inhibitory receptors •  Metabolic state and access to glucose •  Where located?

Tumor •  An:gens/neo-‐an:gens •  Density of pep:de/MHC complexes •  Expression of inhibitory ligands •  Expression of s:mulatory ligands •  Produc:on of inhibitory cytokines •  Produc:on of other inhibitory

substances •  Expression of chemokines •  Innate resistance to ly:c

mechanisms

Stroma/Other Immune Cells •  Treg •  MDSC •  Monocytes/macrophages/APC •  B-‐cells •  NK and NKT cells •  Tumor Vasculature •  Fibroblasts

Host gene:cs Life:me environmental exposures TCR repertoire

Carcinogenesis: Muta:ons Altered gene expression Chronic inflamma:on

Tumor evolu:on Metastases Evolu:on of Tumor-‐Host immune rela:onship

Immune Interven:on Outcome

Pa:ent Presen:ng for Treatment

Tumor microenvironment and Host An:-‐tumor immune response

Issues with the PD-L1 Biomarker

•  Heterogeneity – multiple tumors and multiple passes within a tumor

•  Interval between biopsy and treatment •  Primary versus metastatic disease •  Antibody and staining conditions

•  Defining a positive result (cut-offs): o  Cell type expressing PD-L1 (immune cell

versus tumor or both) o  Location of expression – cell surface versus

intracellular versus stromal o  Intensity, percent of cells ‘positive’ o  Distribution - patchy versus diffuse, intratumoral

versus peripheral

E1L3N SP142

Neg

ativ

e P

ositi

ve

1 mm

H&E

Immunofluorescence shows stroma and epithelial staining are often concordant and adjacent Green = Cytokeratin Blue = Nuclei Red = PD-L1 (SP142)

McLaughlin (Rimm) et al., JAMA Oncology. 2016 Jan 1;2(1):46-54

•  PD-L1 localized with macrophages, dendritic cells and T cells, but not B cells

PD-L1 Expression in Immune Cells and Tumor Cells by Immunofluorescence

PD-L1 / CD163 (macrophage) PD-L1 / CD11c (dendritic cells)

PD-L1 / CD3 (T cells) PD-L1 / CK (tumor)

IC, tumor-infiltrating immune cell; TC, tumor cell. Markers of ICs: CD3, T cells; CD11b, dendritic cells; CD163, macrophages. Marker of TCs: CK, cytokeratin. Red: PD-L1 staining; Green: IC and TC markers; Blue: DAPI staining. Herbst RS et al. Nature 2014;515: 563-567.

Role of sequencing in anti-cancer immunotherapy

Tumor cells: -Mutation load -Neoantigens

-Genomic instability -Mutation

immune mol -Resistance

Immune cells: -TCR seq

-Amount/clones -Specificity -Antigens

Mutation load and change with therapies Class I and Class II neoantigens

Allelic frequency and expression of neoantigens Association with genetic makeup and oncogenic signaling

Expression of immune inhibitory targets Clonal TCR selection and affinity

PD-L1-/TIL- PD-L1-/TIL+ PD-L1+/TIL+ PD-L1+/TIL-

45% Type I

17% Type II

26% Type III

12% Type IV

Four Categories of Tumors Based on Presence of PD-L1 and TILS

Proposed mechanisms associated with NSCLC resistance to anti-PD-1/B7-H1 therapySubgroup

Type Tumor Distribution

Possible Resistance Mechanism(s) Analysis

B7-H1 TIL

- - I 45%Poor priming of general T cell responses

Peripheral CD4+ and CD8+ T cell responses to autologous tumor cells

Lack of inflammatory cell recruitment

Chemokine expression in biopsy or FFPE samples

+ + II 17%Incomplete PD-1/B7-H1 pathway blockade and activation of alternate immune suppressive pathways

CD80 expression on TILs, expression of alternate suppressive pathways in TME

- + III 26% Alternate immune suppressive pathways

Expression of select molecules in pathways with roles in evasion of NSCLC immunity

+ - IV 12% Intrinsic induction of B7-H1 by oncogenes

Expression of molecules triggering aberrant signaling events

Velcheti (Rimm) et al. Lab Invest. 2014 Jan;94(1):107-16.; Chen L. Unpublished 450 samples analyzed

Biomarker Analyses for PD-L1 Treatment Mechanistic studies using pre and post biopsies

Herbst RS et al. Nature 2014;515: 563-567;

Biomarker Analyses Defining the Profile of Non-responders

•  Three distinct patterns of nonresponse were observed •  Most patients who progressed failed to show up-regulation of PD-L1 or

evidence of activated T cells •  These results provide evidence for the “inflamed tumor” hypothesis

CD8 CD8 CD8

CD8 CD8 CD8

Pre

-trea

tmen

t

Pre

-trea

tmen

t

Pre

-trea

tmen

t

On-

treat

men

t wee

k 9

On-

treat

men

t wee

k 6

On-

treat

men

t wee

k 6

Immunologic ignorance Non-functional

immune response Excluded infiltrate



Summary of Responses to MPDL3280A in Paired Biopsies


PD-L1 IC status

CD

8A

GZM

A

GZM

B

IFN

G

CX

CL9

CX

CL1

0

PR

F1

TBX

21

IC3 IC2 IC1 IC0

High PD-L1 IC Staining Is Associated With Preexisting Teff Activation

•  Activated T cells are characterized by expression of CD8, granzymes, perforin, cytokines and other factors

•  This Teff gene signature was associated with PD-L1 IC status

–  2 IFNγ-inducible Th1 chemokines (CXCL9 and CXCL10) notably correlated with IC status (P < 0.0001)

–  CD8+ T-cell infiltration also correlated with IC status (P < 0.001)1

•  CXCL, chemokine (C-X-C motif) ligand; GZM, granzyme, INFG, interferon γ; PRF1, perforin 1; Th1, T helper 1; TBX21, T-box 21. a RNAseq data. Data cutoff: March 14, 2016. 1. Rosenberg Lancet 2016.

13

Rosenberg J, et al. IMvigor210: biomarkers of atezolizumab in mUC. ASCO 2016

10

5

0

-5

Log 2

RN

A E

xpre

ssio

na


PD-L1 IC Status Is Associated With Multiple Immune Inhibitory Regulators

•  Negative regulators of the immune system, such as immune checkpoint proteins and regulatory T cells can dampen the anti-cancer immune response

•  These data suggest that pre-existing adaptive immune response may be suppressed in these patients

•  PD-L1 expression is associated with an activated but potentially suppressed immune response

•  CTLA4, cytotoxic T-lymphocyte–associated antigen; FOXP3, forkhead box P3; HAVCR2, hepatitis A virus cellular receptor 2; IDO1, indoleamine 2,3-dioxygenase 1; LAG3, lymphocyte activation gene 3; TIGIT, T-cell immunoreceptor with immunoglobulin and ITIM domains.

•  a RNAseq data. Data cutoff: March 14, 2016.

14


PD

-L1

LAG

3

HA

VC

R2

CTL

A4

TIG

IT

IDO

1

FOX

P3

CD

244

Log 2

RN

A E

xpre

ssio

na

PD-L1 IC status

10

5

0

-5

IC3 IC2 IC1 IC0


Teff IFNγ-Induced Gene Expression is Associated With Response

•  Higher baseline IFNγ response genes were observed in atezolizumab responders

•  These data are consistent with Th1 and CTL immune responses

•  IFNγ-inducible MHC-I antigen processing and transport genes were also associated with response

•  CTL, cytotoxic T lymphocyte; IRF1, interferon regulatory factor 1; MHC-I, major histocompatibility complex I; PSMB, proteasome subunit β; STAT1, signal transducer and activator of transcription 1; TAP, transporter. a RNAseq data. Data cutoff: March 14, 2016.

15


Log 2

RN

A E

xpre

ssio

na

-4

0

4

8

12

Log 2

RN

A E

xpre

ssio

na

0.0

2.5

5.0

7.5

10.0

PD SD PR CR

RECIST v1.1 response


Luminal

Basal

Urothelium

TCGA Subtype II Is Associated With Higher ORR

•  Gene expression data used to classify IMvigor210 tumor samples recapitulated TCGA subtypes1,2

•  Responses occurred in all subtypes, but ORR was significantly higher in luminal II vs other subtypes (P = 0.0072)

•  TCGA, The Cancer Genome Atlas. Data cutoff: March 14, 2016. 1. Cancer Genome Atlas Research Network Nature 2014. 2. Rosenberg Lancet 2016.


PD SD PR CR


16

0

25

50

75

100

OR

R, %

I II III IV

n = 73 n = 52 n = 38 n = 36

Luminal Basal

Courtesy of Macmillan Publishers Ltd: Choi W, et al. Nat Rev Urol. 2014;11(7):400-410, copyright 2014.


TCGA Subtype II Is Associated With Higher ORR

•  Gene expression data used to classify IMvigor210 tumor samples recapitulated TCGA subtypes1,2

•  Responses occurred in all subtypes, but ORR was significantly higher in luminal II vs other subtypes (P = 0.0072)

•  What might be the drivers of this subtype-specific response?

•  TCGA, The Cancer Genome Atlas. Data cutoff: March 14, 2016. 1. Cancer Genome Atlas Research Network Nature 2014. 2. Rosenberg Lancet 2016.


17

PD SD PR CR


0

25

50

75

100

OR

R, %

I II III IV

n = 73 n = 52 n = 38 n = 36

Luminal Basal


IMvigor210: TCGA Subtype in mUC

•  CDKN2A, cyclin-dependent kinase inhibitor 2A; EGFR, epidermal growth factor receptor; FGFR3, fibroblast growth factor receptor 3; GATA3, GATA-binding protein 3.

•  Data cutoff: March 14, 2016. •  1. Choi Nat Rev Urol 2014. 2.

Aine Sci Rep 2015. 3. The Cancer Genome Atlas Research Network Nature 2014.

Luminal Basal

Papillary like Squamous


Response IC status TC status

FGFR3 CDKN2A KRT5

EGFR GATA3 FOXA1 ERBB2

KRT14

Mesenchymal

TCGA Subtype

I II III IV

18






Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

Mesenchymal

TCGA Subtype

I II III IV

19






Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

Mesenchymal

TCGA Subtype

I II III IV

20



•  Luminal and basal tumors are distinct subtypes with unique histology and gene expression1-3




Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

Mesenchymal

TCGA Subtype

I II III IV

21

Luminal

Basal

Urothelium



•  Luminal I patients have low Teff gene expression

22

Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

CD8A

GZMB GZMA

IFNG CXCL9 CXCL10 PRF1 TBX21

TCGA Subtype

I II III IV

Teff

Mesenchymal

•  Data cutoff: March 14, 2016.

Luminal

Basal

Urothelium



•  Luminal I patients have low Teff gene expression

•  In Luminal II patients with disease progression, a trend toward lower baseline Teff expression was seen, compared with Luminal II responders

23

Luminal Basal I II III IV




FGFR3 CDKN2A KRT5


KRT14

Mesenchymal

CD8A

GZMB GZMA

IFNG CXCL9 CXCL10 PRF1 TBX21

Teff

TCGA Subtype


Luminal

Basal

Urothelium



•  Stromal genes were also analyzed

24

Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

CD8A

GZMB GZMA

IFNG CXCL9 CXCL10 PRF1 TBX21 COL4A1 COL4A2 PDGFRB BGN NUAK1

Stromal

Teff

TCGA Subtype

I II III IV Mesenchymal

•  COL4A, collagen type IV α; PDGFRB, platelet-derived growth factor β. Data cutoff: March 14, 2016.

Luminal

Basal

Urothelium



•  Subtype II patients tended to have lower stromal gene expression

25

Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

Mesenchymal

CD8A

GZMB GZMA


Stromal

Teff

TCGA Subtype

I II III IV


Luminal

Basal

Urothelium



•  Luminal I tumors have low Teff expression

•  Luminal II tumors have high Teff and low stromal gene expression

•  Basal tumors have high Teff and high stromal gene expression

26

Luminal Basal




FGFR3 CDKN2A KRT5


KRT14

Mesenchymal

CD8A

GZMB GZMA


Stromal

Teff

TCGA Subtype

I II III IV


Luminal

Basal

Urothelium



•  IMvigor210 subtypes have distinct tumor-immune landscapes that reflect responsiveness to atezolizumab

•  TIL, tumor-infiltrating lymphocyte. a High myeloid, inflammatory, activated stromal/fibroblast markers. Data cutoff: March 14, 2016.

27

Immune desert Inflamed Immune suppresseda

Increased responses

Tumor cells

TIL/immune cells

Tumor stroma

Luminal Basal

Papillary like Squamous Response IC status TC status

Mesenchymal


I II III IV


Mutation Load Represented by FoundationOne Genes Correlates With Mutation Load in TCGA Whole-Exome Sequencing

•  To estimate mutation load, we used a 315- gene FoundationOne panel that covers ≈ 3% of the exome1

•  Whole-exome results correlated with the FoundationOne regions, indicating that the restricted target region was sufficient to rank patients based on mutation load

UC (bladder) Single-Nucleotide Variants


28

protein altering total

1

10

100

10 1000 10 1000TCGA whole exome

Foun

datio

nOne

(F1)

cap

ture

pan

el

Zero captured:FALSE

TRUE

BLCA somatic mutations (SNVs)

ρ = 0.860a ρ = 0.870a

100

10

1

Foun

datio

nOne

G

enes

Onl

y

10 1000 10 1000 TCGA Whole Exome

•  a Spearman ρ coefficient. Data cutoff: March 14, 2016.

1. Rosenberg Lancet 2016.


•  mUC has a high mutation load and thus potential for neoantigen generation and recognition by the immune system1-3

•  Median load was significantly higher in responders vs non-responders

–  This relationship was statistically independent of other predictors of response

Mutation Load by FoundationOne and Response

•  1. Lawrence Nature 2013. 2. Cancer Genome Atlas Research Network Nature 2014. 3. Kandoth Nature 2013. Data cutoff: March 14, 2016. Rosenberg J, et al. IMvigor210: biomarkers of atezolizumab in mUC. ASCO 2016

29

II III Luminal Basal

IV All (n = 150)

Mut

atio

n Lo

ad/M

B

I 0

10 20

30

40

IC0/1 IC2/3

0

10 20

30

40

50

Mut

atio

n Lo

ad/M

B

responder non-responder


Treg Anti-CCR4, anti-CTLA-4

Adenosine 2AR inhibitors Anti-CD39, anti-CD73

IDO inhibitors, Cox2 inhibitors

Inhibitory Cytokines

MDSC Type 2 macrophages

HDACi, MER-TKi, CCR2i, CSF-1Ri, CKITi, ibrutinib, Anti-CD47 (‘Don’t Eat Me Signals’ )

Checkpoint Inhibitors LAG3, TIM3, TIGIT, B7-H3, B7-H4, PD-1H (Vista), CD200, CEACAM1, KIR

Antibodies and small molecule inhibitors of TGF-beta or its receptors

Metabolic Inhibitors and Prostaglandins

Hypoxia/Adenosine

Activate with TCR-CD3 Constructs (CEA, gp100) Co-opt non-specific TIL

Adoptive Transfer: TIL CAR-T

Vaccines, T-VEC, Anti-CD40, FLT3 TLR agonists, CAR-T

STING agonists Epigenetic Modifiers

Create new tumor-specific T-cells or enhance in vivo Ag presentation

Cytokines and Modified Cytokines

Expansion and Increase Function of Ag-specific T cells

Disrupt tumor barriers to T-cell infiltration Anti-VEGF, anti-SEMA-4D, anti-CTLA-4

Co-stimulatory Agonists – 4-1BB, OX-40, GITR, ICOS, CD27

T-Cell Immune Checkpoints as Targets for Immunotherapy

Adapted from Mellman I et al. Nature. 2011;480:481–489.

CTLA-4

PD-1

TIM-3

BTLA

VISTA LAG-3 HVEM

CD27

CD137

GITR

OX40

CD28

T cell stimulation

Blocking antibodies

Agonistic antibodies

Inhibitory receptors

Activating receptors

T cell

B7-1

T cell

Targeted Therapy

Vaccines

Cell Therapies

Conclusions

•  Luminal type II urothelial cancer appears to be the most responsive to immune checkpoint inhibition

•  Current studies are limited by lack of consective biopsy specimens

Disease Aligned Research Team Retreat and Symposium

checkpoint inhibitors in urothelial cancer: biomarkers and ... · a rnaseq data. data cutoff: march...

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