Il punto di vista dell’esperto

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Fabio Calabrò Oncologia Medica

Azienda Ospedaliera San Camillo Forlanini

Tumori Genito-Urinari


Prostate cancer treatment paradigm is evolving



localized Metastatic CRPC

Metatastic non




Radium-223 Cabazitaxel


*Not licenced

**USA only

Supportive care (eg

denosumab/bisphosphonates) Docetaxel (if no prior use) ADT + Docetaxel*

ADT + Abiraterone*

Rising PSA

Non metatastic CRPC

Local treatment with curative intent +/- adjuvant RT or RT+ADT




Advanced prostate cancer consensus conference 2017

Gillesen S, Eur Urol 2017


Prostate cancer treatment paradigm is evolving

Year Trial/Treatment/Setting mOS

1990 Prednisone M1 mCRPC 12.6

2004 TAX 327 Docetaxel prednisone M1 CRPC 18.9

2010 TROPIC/Cabazitaxel M1 CRPC 29.4

2011 COU-AA-301 Abiraterone post docetaxel M1 CRPC 32.6 2013 COU-AA-302 Abiraterone pre docetaxel M1 CRPC 34.7 2014 PREVAIL Enzalutamide pre docetaxel M1 CRPC 35.3

2015 CHARTEED (ADT + docetaxel M1 HSPC 57.6

2016 STAMPEDE ADT + Docetaxel M1 HSPC 65

2017 LATITUDE STAMPEDE ADT + Abiraterone M1 HSPC nr


Prostate cancer treatment paradigm is evolving


Why Did Patients Live So Long?

Ryan C, Lancet Oncol. 2015; Beer TM, N Engl J Med. 2014

Subsequent Therapy 2

ENZA (n = 872)

Placebo (n = 845)

N (%) with ≥1 subsequent life-extending therapy

457 (52.4%) 685 (81.1%)

Subsequent therapies

Docetaxel 358 (41.1%) 504 (59.6%) Abiraterone acetate 256 (29.4%) 417 (49.3%) Cabazitaxel 79 (9.1%) 149 (17.6%) Enzalutamide* 21 (2.4%) 249 (29.5%) Sipuleucel-T 17 (1.9%) 11 (1.3%)

Radium-223 16 (1.8%) 22 (2.6%)

Subsequent Therapy1

ABI + P (n=546 )

P (n=542) N (%) with selected

subsequent therapy 365 (67%) 435 (80%) Subsequent therapies

Abiraterone 69 (13%) 238 (44%) Cabazitaxel 100 (18%) 105 (19%) Docetaxel 311 (57%) 331 (61%) Enzalutamide 87 (16%) 54 (10%) Ketoconazole 42 (8%) 68 (13%)

Radium-223 20 (4%) 7 (1%)

Sipuleucel-T 45 (8%) 32 (6%)


a. Prometaphase b. Metaphase

c. Anaphase d. Telophase

Taxanes stabilize microtubules leading to cell-cycle arrest in metaphase-anaphase

Jordan & Wilson. Nature Reviews Cancer 2004

Normal cell cycle


Taxanes stabilize microtubules,

inhibit disassembly and inhibit

both ligand-dependent and ligand independent AR transcriptional activity


AR blockade induce proliferation of AR independent clones


Isaacs J et al, The prostate 1984; 5: 1-17

Isaac J, The prostate 1984


Intratumor heterogeneity


Intratumor heterogeneity

Broutos PC, Nat Genetics 2015


SWOG Trial 9346

Hussain M, J Clin Oncol 2006, NEJM 2013

A PSA of 4 ng/mL or less after 7 months of AD is a strong predictor of survival


Halabi S, J Clin Oncol 2014

Prognostic tools


Halabi S, J Clin Oncol 2014

Prognostic tools


Many Nomograms are available


Is an old story

Dawson NA, J Clin Oncol 1998


Author Year published

N pts Duration of 2




≥ 50%

Median PFS


Loriot et al. 2013 38 3 mo 8% 2.7 mo

Noonan et al. 2013 30 13 wks 3% 3.6 mo


Schrader et al. 2013 35 4.9 mo 29% -

Badrising et al. 2014 61 3 mo 21% -

Bianchini et al. 2014 39 2.9 mo 23% -

Schmid et al. 2014 35 2.8 mo 10% -

Brasso et al. 2014 137 3.2 mo 18% -

Cross-resistance between AR-targeted agents

Only retrospective evidence


Integrative landscape analysis of somatic and germline aberrations in mCRPC

 90% of mCRPC harbor clinically actionable

molecular alterations

 20% of mCRPC harbor DNA repair pathway aberrations

 8% harbor germline mutations

Robinson D, Cell. 2015


Distribution of Presumed Pathogenic Germline Mutations

Pritchard CC et al. N Engl J Med 2016;375:443-453

Shown are mutations involving 16 DNA-repair genes

Pritchard, N Engl J Med 2016


Defects in DNA repair genes associated with PARP inhibitor sensitivity

49 heavily pretreated mCRPC men

PARP inhibitor (olaparib 400 mg BID)

Genomic signature of PARP inhibitor sensitivity in 16/49 (33%) pts


Response to PARP in 14/16

Mateo J et al. New Engl J Med. 2015


The begin at the beginning

Yang JC, NEJM 2003


An Era of discovery in RCC


Immunotherapeutic strategies in mRCC

Clinical experience

CTLA-4-directed antibodies. Ipilimumab — a mono- clonal antibody against CTLA-4 — was the first check- point inhibitor to be tested in large-scale trials. It received FDA approval for the treatment of melanoma in 2011, after patients demonstrated superior overall survival in a phase III trial with either ipilimumab alone or in com- bination with the peptide gp100 vaccine compared with vaccine alone33. During its early clinical development, ipilimumab was evaluated for the treatment of advanced RCC. In a phase II trial, 61 patients were treated in one of two dosing cohorts (high or low) for up to 1 year, unless tumour progression or limiting toxicity was observed34. Response rates were 12.5% and 5% in the high-dose and low-dose cohorts, respectively. No complete responses or durable regressions were seen, in contrast to the experi- ence in patients with melanoma. Higher toxicities were recorded for patients in the high-dose group than the low- dose group: 43% of these participants had grade 3, 4, or 5 toxicities compared with 18% for the low-dose group.

Of note, a highly significant positive correlation between development of autoimmune toxicities and response was reported. The response rate for those who experienced toxicities was 30%, compared with 0% of those who did not experience toxicities (P <0.001). This correlation was only observed in a small cohort of patients, but could be important and should be further evaluated in larger phase III trials of checkpoint inhibitors in RCC. Some of the increased toxicity might be attributed to the dos- ing schedule used in this early study — nearly half of the patients who developed toxicities did so after five or more doses. In the phase II studies investigating ipilimumab for melanoma a total of four doses were used, which is now

the widely practiced dosing regimen. Given the improved adverse-effect profile and efficacy of the newer PD-1 inhibitors, CTLA-4 antibody monotherapy in RCC has been largely abandoned in favour of combination trials with other checkpoint inhibitors35.

PD-1-directed antibodies. Nivolumab — a monoclonal antibody that blocks the PD-1 pathway — is the first checkpoint inhibitor to demonstrate a survival benefit in patients with metastatic RCC (TABLE 1). Motivated by the encouraging overall survival results of a dose-ranging phase II nivolumab trial, CheckMate 025 was designed as a phase III, open-label study comparing nivolumab with everolimus in patients with advanced RCC who had failed an anti-VEGF therapy, with overall survival as the primary end point36,37. A total of 821 patients were randomly assigned 1:1 to receive 3 mg/kg of nivolumab every 2 weeks (selected on the basis of its safety and efficacy profile in multiple tumour types) or 10 mg of everolimus daily.

The study was stopped after a prespecified interim analysis determined that the primary end point had been reached. The median overall survival was 25 months for nivolumab and 19.6 months for everolimus37. The over- all survival benefit of nivolumab was present irrespective of Memorial Sloan Kettering Cancer Center risk group, number of previous therapies, or PD-L1 tumour expres- sion level. The objective response rate (ORR) was also higher with nivolumab than everolimus (25% versus 5%), but complete responses were rare — only 1% for nivolumab and <1% for everolimus. Interestingly, the median progression-free survival was similar in both groups (4.6 months for nivolumab and 4.4 months for

Nature Reviews | Urology Single peptide


TG4010 Dendritic cell

AGS-003 Multipeptide


CAR T cells CIK cells





Agonist antibodies




GITR CTLA-4 inhibitors


Tremelimumab PD-1 inhibitors

Nivolumab (FDA approved)


Pidilizumab PD-L1 inhibitors





T-cell agonists Adoptive T-cell therapy

Vaccines Checkpoint inhibitors

Novel immunotherapies being studied for renal cell carcinoma

Figure 1 | Selected immune therapies under investigation for renal cell carcinoma (RCC). Checkpoint inhibitors under investigation include the cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) inhibitors ipilimumab and

tremelimumab, the programmed cell death protein 1 (PD-1) inhibitors nivolumab (which is FDA approved),

pembrolizumab and pidilizumab, and the programmed cell death 1 ligand 1 (PD-L1) inhibitors atezolizumab, BMS-936559, durvalumab, and avelumab. Vaccine strategies investigated in RCC include the single peptide vaccines TroVax® and

TG4010, the dendritic cell vaccine AGS-003, and the multipeptide vaccine IMA901. Adoptive T-cell therapies such as chimeric antigen receptor (CAR) T cells and cytokine-induced killer (CIK) cells are also being investigated. Multiple T-cell agonists have been or are being studied, including the cytokines IL-2, IFNγ, and IL-21, as well as agonist antibodies to the co-stimulatory molecules CD137, OX40, CD27 and GITR.


422 | JULY 2016 | VOLUME 13 nrurol


Combinatorial explosion

Ledford H, Nature 2016


First Line Phase III Trials


Locally advanced or mRCC

Previously untreated with any systemic therapy

Karnofsky PS ≥70 Sunitinib

50 mg PO daily, 4 weeks on/2 weeks off

Phase III N=1070 CheckMate214 - NCT02231749: Combination PD-1 + CTLA-4 inhibition


Co-Primary endpoint: PFS, OS


Locally advanced or mRCC with

clear-cell and/or sarcomatoid component

Previously untreated with any systemic therapy

Karnofsky PS ≥70 Sunitinib

50 mg PO daily, 4 weeks on/2 weeks off

Phase III N=900 IMmotion 151 - NCT02420821: Combination PD-L1 + VEGF inhibition


Co-Primary endpoint: PFS, OS


Locally advanced or mRCC with clear cell component

Previously untreated with any systemic therapy

Karnofsky PS ≥70 Sunitinib

50 mg PO daily, 4 weeks on/2 weeks off

Phase III N=583 Javelin Renal 101 - NCT02684006: Combination PD-L1 + VEGFR TKI


Primary endpoint: PFS

Nivolumab + Ipilimumab

3mg/kg IV + 1mg/kg IV every 3 weeks X4

then Nivolumab 3mg/kg IV q2w

Atezolizumab + Bevacizumab 1200 mg IV +

15 mg/kg IV q3w

Avelumab + Axitinib 10mg/kg IV q2w

+ 5mg PO BID


First Line Phase III Trials


Advanced/mRCC, predominantly clear cell histology

Previously untreated with any systemic therapy

Karnofsky PS ≥70 Sunitinib

Phase III N=450 ADAPT - NCT01582672: Autologous Dendritic Cell Vaccine


Primary endpoint: OS Eligibility:

Advanced/mRCC with clear cell component

Previously untreated with any systemic therapy

Karnofsky PS ≥70


50 mg PO daily, 4 weeks on/2 weeks off

Phase III N=840 KEYNOTE 426 - NCT02853331: Pembrolizumab + Axitinib


Co-Primary endpoint: PFS, OS

Pembrolizumab + Axitinib 200 mg IV every 3 weeks +

5 mg PO BID


Advanced/mRCC with clear cell component

Previously untreated with any systemic therapy

Karnofsky PS ≥70 Sunitinib

50 mg PO daily, 4 weeks on/2 weeks off

Phase III N=735 NCT02811861: Lenvatinib + Everolimus or Pembrolizumab


Primary endpoint: PFS

Lenvatinib + Everolimus 18 mg PO daily +

5 mg PO daily

Lenvatinib + Pembrolizumab 20 mg PO daily +

200 mg IV q3w


8 intradermal injections in first year followed by quarterly boosters


Nuzzo R. Nature 2014


Management of metastatic UC until 2016

Management of metastatic UC until 2016

Cisplatin-eligible patients Cisplatin-ineligible patients

Dose-dense MVAC

Cisplatin- gemcitabine

Carboplatin- gemcitabine

Single-agent Or BSC

First-line metastatic urothelial cancer

Platinum-resistant metastatic urothelial cancer

No standard chemotherapy: Vinflunine and taxanes are options


How do these data translate in clinical practice? How do these data translate in clinical practice in the moving landscape of mUC ?

FDA approval EMA approval


Pembrolizumab (benefit on OS) Nivolumab

Avelumab Durvalumab Atezolizumab Pembrolizumab

Nivolumab Atezolizumab pembrolizumab 1st line

2nd line




Open questions and problems with immunotherapy

FDA approvals

Lack of predictive biomarkers

Treatment beyond progression

Hyperprogressive disease

Treatment option for patients who progress on CPI

Trial design and interpretation


ORR by PD-L1 status

Drug Phase setting n PD-L1


ORR in favorable

ORR in negative

CR %

Atezolizumab 1 Post DDP 67 IC 2/3 43% 11% 7/0

Atezolizumab 2 Post DDP 315 IC 2/3 28% 11% 11/2

Atezolizumab 2 DDP unfit 119 IC2/3 28% 21% 3/5

Atezolizumab 3 Post DDP 912 IC 2/3 23% NR 8/0

Nivolumab 1/2 Post DDP 78 PD-L1>1% 24% 26% 1/4

Nivolumab 2 Post DDP 270 PD-L1>1% or 5%

23% 16% 4/0

Durvalumab 1 Post DDP 61 PD-L1 TC or IC


46% 0 NR

Avelumab 1b Post DDP 44 PD-L1>5% 25% 13% NR

Pembrolizumab 1b Post DDP 33 PD-L1>1% in TC 14% 27% NR

Pembrolizumab 2 DDP unfit 100 CPS>10% 51% 23% 13/5

Pembrolizumab 3 Post DDP 542 CPS> 10% 20% NR 8/NR


Outcome by subtypes

Drug Phase Setting n Better results in

Atezolizumab 1 Post DDP 67 ECOG PS=-1, smokers, no visceral mets

Atezolizumab 2 Post DDP 315 ECOG PS 0, LN only, high mutational load, Luminal II TCGA

Atezolizumab 2 DDP unfit 119 Upper tract, LN only, perioperative CT, TCGA luminal

Atezolizumab 3 Post DDP 912 Current smoker, urethra primary, LN only

Nivolumab 1/2 Post DDP 78 No visceral mets, LN only, Hb > 10

Nivolumab 2 Post DDP 270 Basal I and luminal II, 25 genes IGN gamma signature

Avelumab 1b Post DDP 44 No viscetal mets, HB > 10, > 3 lines of CT

Pembrolizumab 2 DDP unfit 100 Liver mets, upper tract, visceral disease, T cell inflamed GEP signature

Pembrolizumab 3 Post DDP 542 Current smokers, PS=2, LN only,

preoperatiove CT


Association among TCGA subtype, mutation load and clinical activity

C: Mutation load as a fuction of response D: Mutation load versus response disaggregated by subtype or PD-L1 IC score

E: Kaplan-Meier estimate of overall survival according to

estimated mutation load (per megabase), binned into quartile (log-rank p=0.0041for a difference in overall survival between quartiles 1-3 and quartile 4

Balar AV et al., Lancet. 2017


Predictors of response to Atezolizumab Predictors of Response to Atezolizumab

PD-L1 IHC, TCGA subtype and mutation load were significant independent

predictors of response

PD-L1 IC + subtype combination

significantly improved on PD-L1 IC alone or subtype alone

3-biomarker combination

significantly improved on PD-L1 IC + subtype combination

These data highlight the importance of the interaction between the tumor and its microenvironment in understanding response to atezolizumab


P = 0.0109

TCGA Subtype

P = 0.0384

Mutation Load

P < 0.0001

P = 0.0229 P = 0.0057

P = 0.0005

P = 0.0935

Based on data cutoff: March 14, 2016.

Rosenberg J, et al. IMvigor210: biomarkers of atezolizumab in mUC. ASCO 2016 PD-L1 IC

+ TCGA Subtype

PD-L1 IC + TCGA Subtype + Mutation Load

Rosenberg J. ASCO 2016


Outcome of Patients Treated Beyond Progression


Subsequent reductions in target lesion SLD were seen in patients treated with atezolizumab beyond progression, highlighting the potential the potential for non -classical responses

Patients without post-PD baseline tumor assessments (n = 29) are not included in plot. Data cutoff: March 14, 2016.

Dreicer R, J Clin Oncol 2016 In patients treated beyond PD

•19% (26/134) had SLD reductions ≥ 30% in target lesions

•28% (38/134) had disease stabilization (> -30% to +20% SLD change)

•mOS was 11.4 mo in all patients treated beyond progression

•12-mo OS was 50% in all patients treated beyond progression

•The safety of atezolizumab was consistent with that in the ITT population


Hyperprogressive disease

Champiat S, Clin Cancer Res 2016


Not associated with higher tumor burden

Associated with increased age

Worse outcome

Slower growing tumors less likely to respond


Immunotherapy combinations in urothelial cancer

Study Arms Line of


n Phase

IMvigor 130 Atezolizumab vs atezolizumab + platinum based CT vs platinum based CT

1st 1200 3

KEYNOTE 361 Pembrolizumab +/- platinum based combination CT vs CT 1st 990 3 BISCAY Durvalumab +/- targeted agent matched to tu or profile

FGFR, PARP, PI3K inhibitor

1, 2, 3 140 1b/2

NCI Nivolumab + Cabozantinib +/- ipilimumab 2nd 66 1/2

BMS CA224-020 Anti-LAG3 +/- nivolumab 2nd 30 1

Celldex CDX1127- 06

Varlilumab + atezolizumab 2nd 55 1

CORVUS CPI-444- 001

CPI-444 +/- atezolizumab 2nd 534 1



Enadenotucirec (oncolytic virus) + nivolumab 2nd 30 1

Yale Ramuvirumab + pembrolizumab 2nd 155 1

Plexxicon CSF1R, KIT or FLT3 inhibitor + pembrolizumab 2nd 400 1/2

USC Pembrolizumab + sEphB4-HSA 2nd 60 2


Multiple factors influence tolerance and immunity

Chen DS and Mellman I, Nature 2017


Factors influencing the cancer-immune set point

Chen DS and Mellman I, Nature 2017


A stochastic process


Cancer evolution

Mutation, selection and drift

Lipinski KA, Trends in Cancer 2016



 None of the trials address the question of combinations vs sequences

 Patient selection remains undefined

 Is combination therapy suitable for every patient?

 Will we cure patients?

 What will be our strategy after combination?

 The pace of immunotherapy studies has outstripped our understanding of the underlying basic science

 The inundation of clinical trial will (hopefully) help in defining the optimal sequence, combination and duration of therapy

 The stochastic nature of cancer must be taken into account




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