Tumori Genito-Urinari Fabio Calabrò Oncologia Medica Azienda Ospedaliera San Camillo Forlanini
Prostate cancer treatment paradigm is evolving PROSTATE CANCER TREATMENT PARADIGMIS EVOLVING Non metatasticcrpc Clinically localized Rising PSA? Metastatic CRPC Local treatment with curative intent +/- adjuvant RT or RT+ADT? ADT + ADT + Metatasticnon castrate Docetaxel* Abiraterone* Abiraterone Enzalutamide Docetaxel (if no prior use) Cabazitaxel Radium-223 Sipuleucel-T** *Not licenced **USA only Supportive care (eg denosumab/bisphosphonates)
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? Subsequent Therapy 1 ABI + P (n=546 ) P (n=542) Subsequent Therapy 2 ENZA (n = 872) Placebo (n = 845) N (%) with selected subsequent therapy Subsequent therapies 365 (67%) 435 (80%) 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%) N (%) with 1 subsequent life-extending therapy Subsequent therapies 457 (52.4%) 685 (81.1%) 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%) Ryan C, Lancet Oncol. 2015; Beer TM, N Engl J Med. 2014
Taxanes stabilize microtubules leading to cell-cycle arrest in metaphase-anaphase Normal cell cycle a. Prometaphase b. Metaphase c. Anaphase d. Telophase Taxanes Taxanes stabilize microtubules, inhibit disassembly and inhibit both ligand-dependent and ligand independent AR transcriptional activity Jordan & Wilson. Nature Reviews Cancer 2004
AR blockade induce proliferation of AR independent clones R-BLOCKADE INDUCE PROLIFERATION OF AR- DEPENDENT 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 A PSA of 4 ng/ml or less after 7 months of AD is a strong predictor of survival Hussain M, J Clin Oncol 2006, NEJM 2013
Prognostic tools Halabi S, J Clin Oncol 2014
Prognostic tools Halabi S, J Clin Oncol 2014
Many Nomograms are available
Is an old story Dawson NA, J Clin Oncol 1998
Cross-resistance between AR-targeted agents Only retrospective evidence Author Year published N pts Duration of 2 nd treatment PSA 50% Median PFS ENZ ABI Loriot et al. 2013 38 3 mo 8% 2.7 mo Noonan et al. 2013 30 13 wks 3% 3.6 mo ABI ENZ 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% -
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 BRCA2, ATM, BRCA1, PALB2, CHEK2, FANCA, HDAC2 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
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 Immunotherapeutic strategies in mrcc S Novel immunotherapies being studied for renal cell carcinoma Checkpoint inhibitors Vaccines Adoptive T-cell therapy T-cell agonists CTLA-4 inhibitors Ipilimumab Tremelimumab PD-1 inhibitors Nivolumab (FDA approved) Pembrolizumab Pidilizumab PD-L1 inhibitors Atezolizumab BMS-936559 Durvalumab Avelumab Single peptide TroVax TG4010 Dendritic cell AGS-003 Multipeptide IMA901 CAR T cells CIK cells Cytokines IL-2 IFN-g IL-21 Agonist antibodies CD137 OX40 CD27 GITR
Combinatorial explosion Ledford H, Nature 2016
First Line Phase III Trials CheckMate214 - NCT02231749: Combination PD-1 + CTLA-4 inhibition Eligibility: Locally advanced or mrcc Previously untreated with any systemic therapy Karnofsky PS 70 RANDOMIZATION Phase III N=1070 Nivolumab + Ipilimumab 3mg/kg IV + 1mg/kg IV every 3 weeks X4 then Nivolumab 3mg/kg IV q2w Sunitinib 50 mg PO daily, 4 weeks on/2 weeks off Co-Primary endpoint: PFS, OS IMmotion 151 - NCT02420821: Combination PD-L1 + VEGF inhibition Eligibility: Locally advanced or mrcc with clear-cell and/or sarcomatoid component Previously untreated with any systemic therapy Karnofsky PS 70 RANDOMIZATION Phase III N=900 Atezolizumab + Bevacizumab 1200 mg IV + 15 mg/kg IV q3w Sunitinib 50 mg PO daily, 4 weeks on/2 weeks off Co-Primary endpoint: PFS, OS Javelin Renal 101 - NCT02684006: Combination PD-L1 + VEGFR TKI Eligibility: Locally advanced or mrcc with clear cell component Previously untreated with any systemic therapy Karnofsky PS 70 Primary endpoint: PFS RANDOMIZATION Phase III N=583 Avelumab + Axitinib 10mg/kg IV q2w + 5mg PO BID Sunitinib 50 mg PO daily, 4 weeks on/2 weeks off
First Line Phase III Trials KEYNOTE 426 - NCT02853331: Pembrolizumab + Axitinib Eligibility: Advanced/mRCC with clear cell component Previously untreated with any systemic therapy Karnofsky PS 70 Co-Primary endpoint: PFS, OS RANDOMIZATION Phase III N=840 Pembrolizumab + Axitinib 200 mg IV every 3 weeks + 5 mg PO BID Sunitinib 50 mg PO daily, 4 weeks on/2 weeks off NCT02811861: Lenvatinib + Everolimus or Pembrolizumab Eligibility: Advanced/mRCC with clear cell component Previously untreated with any systemic therapy Karnofsky PS 70 Sunitinib Primary endpoint: PFS 50 mg PO daily, 4 weeks on/2 weeks off ADAPT - NCT01582672: Autologous Dendritic Cell Vaccine Eligibility: Advanced/mRCC, predominantly clear cell histology Previously untreated with any systemic therapy RANDOMIZATION Phase III N=450 Karnofsky PS 70 Sunitinib Primary endpoint: OS RANDOMIZATION Phase III N=735 Lenvatinib + Everolimus 18 mg PO daily + 5 mg PO daily Lenvatinib + Pembrolizumab 20 mg PO daily + 200 mg IV q3w AGS-003 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 First-line metastatic urothelial cancer Cisplatin-eligible patients Cisplatin-ineligible patients Dose-dense MVAC Cisplatingemcitabine Carboplatingemcitabine Single-agent Or BSC Platinum-resistant metastatic urothelial cancer No standard chemotherapy: Vinflunine and taxanes are options
How do these data translate in clinical practice? FDA approval EMA approval 1st line Atezolizumab Pembrolizumab Atezolizumab pembrolizumab 2nd line Atezolizumab Pembrolizumab (benefit on OS) Nivolumab Avelumab Durvalumab Nivolumab Atezolizumab pembrolizumab
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 definition 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% Durvalumab 1 Post DDP 61 PD-L1 TC or IC >25% 23% 16% 4/0 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 IC TCGA Subtype P = 0.0109 P = 0.0384 P = 0.0229 P = 0.0057 Mutation Load P < 0.0001 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 PD-L1 IC + TCGA Subtype P = 0.0005 PD-L1 IC + TCGA Subtype + Mutation Load P = 0.0935 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 Based on data cutoff: March 14, 2016. Rosenberg J, et al. IMvigor210: biomarkers of atezolizumab in muc. ASCO 2016 Rosenberg J. ASCO 2016
Outcome of Patients Treated Beyond Progression (n=134) Subsequent reductions in target lesion SLD were seen in patients treated with atezolizumab beyond progression, highlighting the potential the potential for non -classical responses 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 Patients without post-pd baseline tumor assessments (n = 29) are not included in plot. Data cutoff: March 14, 2016. The safety of atezolizumab was consistent with that in the ITT population Dreicer R, J Clin Oncol 2016
Hyperprogressive disease 10% Not associated with higher tumor burden Associated with increased age Worse outcome Slower growing tumors less likely to respond Champiat S, Clin Cancer Res 2016
Immunotherapy combinations in urothelial cancer Study Arms Line of therapy IMvigor 130 Atezolizumab vs atezolizumab + platinum based CT vs platinum based CT n Phase 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 CORVUS CPI-444-001 PsiOxus Therapeutics Varlilumab + atezolizumab 2nd 55 1 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
Conclusions 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