Daniel Castellano Oncología Médica. Unidad de Tumores Genito-Urinarios
Hospital Universitario 12 de Octubre I + 12 Research Institute
Actualización en el tratamiento de Cáncer Renal
Avanzado
epidemiología
2-3% del total de tumores malignos Edad media de aparición: 65 años
epidemiología
-Tabaquismo - Obesidad - Hipertensión arterial - Otros (menos claros):
- - - -
Exposición a tóxicos (asbestos) Enfermedad renal crónica – diálisis Poliquistosis renal Infección crónica por hepatitis C
Factores Pronósticos
• Síndrome Von Hippel-Lindau se caracteriza por mutación del gen VHL y desarrollo de tumores vasculares incluido CCR.
• La función normal del gen VHL (pVHL) es ayudar a destruir HIFa dentro de la célula.
• Mutación del genVHL (90% somática) conduce a una pVHL modificada no funcionante que permite incremento de niveles intracel. de HIFa y b.
• Sobre-expresión de HIFa induce expresión de genes hipoxia tisular.
• Sobre-expresión consecuente de VEGF, PDGF,TGF promueve angiogenesis tumoral y proliferación.
Rini, et al. Lancet Oncol. 2009;10:992-1000.
Pazopanib
MSKCC criteria
Karnofsky PS <80
Low serum hemoglobin
High corrected calcium
High LDH
Time from diagnosis to treatment <1 year
Motzer RJ, et al. J Clin Oncol 2002; Hudes G, et al. N Engl J Med 2007
MSKCC Risk prognostic model for RCC
MSKCC Risk prognostic model for RCC
= Grupo Buen Pronóstico = Grupo Intermedio Pronóstico
= Grupo Mal Pronóstico
Motzer RJ, et al. J Clin Oncol 2002; Hudes G, et al. N Engl J Med 2007
aRCC, advanced renal cell carcinoma; FDA, US Food and Drug Administration; IFN-α, interferon α; IL-2, interleukin-2; mTOR, mammalian target of rapamycin; VEGF, vascular endothelial growth factor. *Approved by the FDA in RCC. 1. Escudier B et al. N Engl J Med. 2007;356:125-134. 2. Motzer RJ et al. N Engl J Med. 2007;356:115-124. 3. Hudes G et al. N Engl J Med. 2007;356:2271-2281. 4. Motzer RJ et al. Lancet. 2008;372:449-456. 5. Escudier B et al. Lancet. 2007;370:2103-2111. 6. Rini BI et al. J Clin Oncol. 2008;26:5422-5428. 7. Sternberg CN et al. J Clin Oncol. 2010;28:1061-1068. 8. Rini BI et al. Lancet. 2011;378:1931-1939. 9. Motzer RJ et al. N Engl J Med. 2015;373(19):1803-1813.
IFN-α
1992–
2005
High-dose IL-2
Cytokines
Pazopanib7
Temsirolimus3
Sorafenib1
Everolimus4
Axitinib8
Bevacizumab + IFN-α5,6
Sunitinib2
2009 2010 2007 2011 2008 2012
VEGF- and mTOR-Targeted therapies (based on FDA approval dates)
2006 2016
Nivolumab9*
Investigational therapies
Nivolumab + Ipilimumab?
2018
Cabozantinib*
2018+
Lenvatinib*
Atezolizumab + Bevacizumab?
Avelumab + Axitinib
Pembro + Axitinib
The Evolving Treatment Landscape of RCC
Agent n Median PFS
(months) Median OS (months) ORR (%)
Sunitinib vs IFN-α1 750 11 vs 5 p<0.001
26.4 vs 21.8 p=0.051
47 vs 12 p<0.001
Bevacizumab + IFN-α vs IFN-α2,3 649 10.2 vs 5.4 p<0.0001
23.3 vs 21.3 p=0.1291
31 vs 13 p=0.0001
Bevacizumab + IFN-α vs IFN-α4,5 732 8.5 vs 5.2 p<0.0001
18.3 vs 17.4 p=0.069
26 vs 13 p<0.0001
Pazopanib vs placebo6,7 435 11.1 vs 2.8 p<0.0001
22.9 vs 20.5* p=0.224
30 vs 3* p<0.001
Poor-risk patients
Temsirolimus vs IFN-α8† 626 5.5 vs 3.1 p<0.001
10.9 vs 7.3 p=0.008
8.6 vs 4.8 NS
*Includes cytokine refractory and treatment-naïve patients; †Poor-risk patients (modified MSKCC criteria) NS, not studied
Recommended targeted agents for first-line treatment: Results from pivotal trials
1. Motzer RJ, et al. J Clin Oncol 2009;27:3584–90; 2. Escudier B, et al. Lancet 2007;370:2103–11; 3. Escudier B, et al. J Clin Oncol 2010;28:2144–50; 4. Rini BI, et al. J Clin Oncol 2008;26:5422–8; 5. Rini BI, et al. J Clin Oncol 2010;28:2137–43; 6. Sternberg C, et al. J Clin Oncol 2010;28:1061–8; 7. Sternberg C, et al. Eur J Cancer 2013;49:1287–96; 8. Hudes G, et al. New Engl J Med 2007;356:2271–81
Modelos Integrados de Predicción Pronóstica en CCR avanzado
Grupo Buen Pronóstico Grupo Intermedio Pronóstico Grupo Mal Pronóstico
MSKCC criteria
Karnofsky PS <80
Low serum hemoglobin
High corrected calcium
High LDH
Time from diagnosis to treatment <1 year
5
VEGFR-2 VEGFR-1
PDGFR-α VEGFR-3 PDGFR-ß c-Kit Flt-3
Overview of TKI´s agents in mRCC Anti-angiogenesis Bevacizumab VEGF-A VEGF-B VEGF-C VEGF-D VEGF-E
Pazopanib Sorafenib Raf Sunitinib
Preclinical in vitro data need to be validated in a clinical setting References are in slide notes
ESMO Guidelines 2015
Patterns of tumor progression on VEGF or VEGFR inhibitors
Chan
ge in
Tum
or
Mea
sure
men
ts (
%)
Chan
ge in
Tum
or
Mea
sure
men
ts (
%)
Chan
ge in
Tum
or
Mea
sure
men
ts (
%)
Primary refractory Early progressors Late progressors
Group A Group B Group C
Trial TARGET[1]
Experimental Arm Sorafenib
Control Arm Placebo
Study Eligibility 2L, after systemic tx
N 903
ORR, % PR: 10% vs 2%*
mPFS, mo 5.5 vs 2.8*
mOS, mo 19.3 vs 15.9
INTORSECT[2] Temsirolimus Sorafenib 2L, after sunitinib 512 8% vs 8% 4.3 vs 3.9 12.3 vs 16.6*†
RECORD-1[3] VEG105192[4,5] AXIS[6,7]
Everolimus Pazopanib Axitinib
Placebo Placebo Sorafenib
2L, after systemic tx 1L/2L 2L, after systemic tx
416 435 723
PR: 1.8% vs 0% 30% vs 3%* PR: 19% vs 9%*
4.9 vs 1.9* 9.2 vs 4.2* 6.8 vs 4.7*
14.8 vs 14.4 22.9 vs 20.5 20.1 vs 19.2
1. 2. 3. 4. 5. 6. 7.
• Despite significant mPFS improvements, mOS changes were generally not significant[1-6] Escudier B et al. N Engl J Med. 2007;356(2):125-134. Hutson TE et al. J Clin Oncol. 2014;32(8):760-767. Motzer RJ et al. Cancer. 2010;116(18):4256-4265. Sternberg CN et al. Eur J Cancer. 2013;49(6):1287-1296. Sternberg CN et al. J Clin Oncol. 2010;28(6):1061-1068. Motzer RJ et al. Lancet Oncol. 2013;14(6):552-562. INLYTA. Summary of product characteristics.
Recommended targeted agents for second-line treatment: Results from pivotal trials
AXIS1032: Axitinib pivotal trial in second-line setting
Primary endpoint: PFS
Rini BI, et al. Lancet 2011;378:1931–9
ECOG PS, Eastern Cooperative Oncology Group performance status; *Starting dose 5 mg BID with option for dose titration to 10 mg BID
Axitinib 5 mg BID*
Sorafenib 400 mg BID
n=723
R A N D O M I S E
1:1
Eligibility: mRCC clear-cell
histology Failure of one first-line
regimen containing: ‒ Sunitinib
‒ Bevacizumab + IFN-α
‒ Temsirolimus, or ‒ Cytokines
Stratification by prior regimen and ECOG PS
First Phase III, head-to-head study vs a targeted agent in second-line mRCC
> RR of axitinib in comparison with sorafenib
Mejor tasa de respuesta % Axitinib Sorafenib
Respuesta Parcial* Estabilización de la enfermedad Progresión de la enfermedad Indeterminado
19.4 49.9 21.6 6.1
9.4 54.4 21.0 11.6
Risk ratio (95% CI) 2.1 (1.4–3.0)
*Axitinib vs. sorafenib: P = 0.0001
Rini B, et al. ASCO 2011
Axitinib European SmPC
Axitinib* showed greater efficacy in extending mPFS vs sorafenib
0 2 4 6 8 10 12 14 16 18 20
1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0
Time (months)
p< 0.0001 (log-rank) Stratified HR 0.67 (95% CI, 0.56, 0.81)
Axitinib Sorafenib
mPFS, mo 95% CI 6.8 4.7
6.4, 8.3 4.6, 6.3
PFS
(pro
babi
lity)
PFS in overall ITT population
90% power to show improvement in PFS using a one-sided log-rank test at a significance of 0.025 *Axitinib is indicated for advanced RCC after failure of prior treatment with sunitinib or a cytokine; ITT, intention-to-treat; mPFS, median progression-free survival
For Internal Use Only
AXIS Study: PFS by Prior Regimen
Prior Treatment Regimen
Axitinib (n = 361)
Sorafenib (n = 362) HR* P
Cytokines (n = 251)
IRC 12.1 6.5 0.464 < 0.0001
Investigator 12.0 8.3 0.636 0.005 Sunitinib (n = 389)
IRC 4.8 3.4 0.741 0.011 Investigator 6.5 4.5 0.636 0.0002
Temsirolimus (n = 24) IRC 10.1 5.3 0.511 0.143 Investigator 2.6 5.7 1.210 0.634
Bevacizumab (n = 59) IRC 4.2 4.7 1.147 0.637 Investigator 6.5 4.5 0.753 0.213
22
*One-sided log-rank test stratified by ECOG PS. Rini BI et al. Lancet. 2011;378(9807):1931-1939.
23
Everolimus + BSC (n=272)
Placebo + BSC (n=138)
Si hay progresión
A L E A T O R I Z A C I Ó
NN
2:1
• CCR metastático de células claras
• 1 o 2 regímenes previos de VEGFR-TKI
1er Análisis interino 2º Análisis interino Análisis final =
N=416
Motzer RJ, et al. Lancet. 2008; Escudier B, et al. ESMO 2008; Motzer RJ, et al. ASCO GU 2009
RECORD-1: Resultados (I)
SLP (todos los pacientes)
1.0
0.8
0.6
0.4
0.2
0
Pro
porc
ión
sin
prog
resi
ón
Tiempo meses 0 2 4 6 8 10 12 14
Pacientes en riesgo Everolimus 277 192 115 51 26 10 1 0 Placebo 139 47 15 6 2 0 0 0
Mediana de SLP (meses) Everolimus: 4.90 Placebo: 1.87 HR=0.33 (95% IC: 0.25–0.43) Log-rank P=<0.001 Everolimus Placebo
SG (todos los pacientes)
1.0
0.8
0.6
0.4
0.2
0 0 2 4 6 8 10 12 14 16 18 20 22 24
Pacientes en riesgo Everolimus 227 267 240 204 164 155 131 101 61 30 6 0 0 Placebo 139 131 117 100 88 74 56 43 27 13 3 0 0
Mediana SG (meses) Everolimus: 14.78 Placebo: 14.39 HR=0.87 (95% IC: 0.65–1.17) Log-rank P=<0.001 Everolimus Placebo
Pro
porc
ión
sin
prog
resi
ón
Tiempo meses
BSC = mejor tratamiento de soporte
For Internal Use Only
RECORD-1 Subgroup Analysis: 1 or 2 Previous VEGFr-TKIs
Calvo E et al. Eur J Cancer. 2012;48:333-339.
100
80
60
40
20
0
1 2 3 4 0 5 6 7 8 9 10 1 1 12 13 14
188 143 121 87 205 71 43 36 22 19 8 6 1 0 0
Number of patients at risk Everolimus
Time, months
Prob
abili
ty, %
Everolimus (n = 205), 1 previous VEGFr-TKI Everolimus (n = 72), 2 previous VEGFr-TKIs
67 49 44 28 72 21 8 7 4 3 2 2 0 0 0 Everolimus
One previous VEGFr-TKI: 5.4 months everolimus vs 1.9 months placebo (HR, 0.32; 95% CI, 0.24–0.43; P < 0.001). Two previous VEGFr-TKIs: 4.0 months everolimus vs 1.8 months placebo (HR, 0.32; 95% CI, 0.19–0.54; P < 0.001).
Median PFS:
24
E07080- VEGFR2/FGFR inhibitor
Stratification factors:
•
•
Hemoglobin (normal vs low) Corrected serum calcium (≥ vs < 10 mg/dL)
Key eligibility criteria: •Advanced or metastatic RCC
•Measurable disease
•Progression on/after 1 prior VEGF-targeted therapy •Progression within 9 mos of stopping prior treatment •ECOG PS ≤1
10 mg PO qd
Study Design
Lenvatinib 18 mg PO qd
+
Everolimus
5 mg PO qd
Lenvatinib
24 mg PO qd
Everolimus
Patients were treated until: • Disease progression
• Unacceptable toxicity
R A N D O M I Z E
Patient Characteristics and Prior Therapy
Lenvatinib/Everolimus (n = 51)
Lenvatinib (n = 52)
Everolimus (n = 50)
MSKCC risk group, %
Favorable Intermediate Poor
24 37 39
21 35 44
24 38 38
Prior VEGF-targeted therapy*, %
Sunitinib Pazopanib Sorafenib Other
71 18 2 10
67 25 0 8
56 26 4 14
*Lenvatinib/Everolimus total sum exceeds 100% due to rounding In total, 5 patients had prior checkpoint inhibitor therapy and 14 patients had prior cytokine therapy
Prog
ress
ion-
free
Sur
viva
l
Number at risk Lenvatinib/Everolimus Lenvatinib Everolimus
51 52 50
41 41 29
27 29 15
23 20 11
16 11 7
10 6 3
5 4 1
1 1 0
0 0 0
Primary Endpoint: Prog.-free Survival Median, mos (95% CI)
Lenvatinib/Everolimus 14.6 (5.9–20.1)
Lenvatinib Everolimus
7.4 (5.6–10.2)
5.5 (3.5–7.1)
1.0
0.8 0.6 0.4
0.2 0.0
Time (mos) 0 3 6 9 12 15 18 21 24
Lenvatinib/Everolimus vs Everolimus HR 0.40 (95% CI 0.24–0.68); P < 0.001 Lenvatinib vs Everolimus HR 0.61 (95% CI 0.38–0.98); P = 0.048
Summary of Efficacy
Lenvatinib/Everolimus (n = 51)
Lenvatinib (n = 52)
Everolimus (n = 50)
Progression-free survival
Median (mo) 95% CI Benefit vs everolimus Objective response rate, % 95% CI Benefit vs everolimus
14.6 5.9–20.1 P < 0.001 43 29–58 P < 0.001
7.4 5.6–10.2 P = 0.048 27 16–41 P = 0.007
5.5 3.5–7.1 NA 6 1–17 NA
Overall survival (updated)
Median (mo) 95% CI Benefit vs everolimus
25.5 16.4–NE P = 0.024
19.1 13.6–26.2 P = 0.118
15.4 11.8–19.6 NA
NA, not applicable; NE, not estimable.
METEOR: Phase III study of second-line treatment with cabozantinib vs everolimus in mRCC
• • • •
Primary endpoints: PFS Secondary endpoints: OS, ORR Exploratory endpoints: patient-reported outcomes, biomarkers, safety, PK Stratification: MSKCC risk group, number prior VEGFR TKI
RA ND O M I SA T I ON
1. www.clinicaltrials.gov (NCT01865747); 2. http://www.meteorclinicaltrial.com
Eligibility1,2
mRCC with clear cell component Mensurable disease
Progression on prior VEGFR TKI within 6 mon of enrollment No limit to the number of prior therapies PD-1/PD-L1 allowed
Brain metastases allowed if treated
N=650
Cabozantinib 60 mg po daily
(n~325) Everolimus 10 mg po daily (n~325) No cross-over allowed
Escudier B, et al. ASCO GU 2016
Escudier B, et al. ASCO GU 2016
METEOR: PFS in Subgroups (independent radiology review committee)
Escudier B, et al. ASCO GU 2016
METEOR: All cause adverse events
METEOR: Phase III study of second-line treatment with cabozantinib vs everolimus in mRCC
Escudier B, et al. ASCO GU 2016
New agents in clinical development for RCC
Novel agent Target /MoA Combined with Status Presenting author
Abstract Nº
Aflibercept (AVE0005)
VEGF-A SINGLE AGENT Phase 2 completed
Pili 4549
Buparlisip (BKM120)
PI3K Plus bevacizumab Phase 1 completed
Mc Kay 4559
CRLX101 HIF, topo-I Plus bevacizumab Phase 2 ongoing
Keefe, Voss 4543, TPS4579
Dalantercept ALK1 Plus axitinib Phase 2 ongoing
Voss 4567, TPS4583
Lenvatinib (E7080)
VEGFR2, FGFR, PDGFR
Plus everolimus Phase 2 completed
Motzer 4506
LY2510924 CXCR4 Plus sunitinib Phase 2 completed
Hainsworth 4547
RX-0201 AKT1 Plus everolimus Phase 1 completed
Peterson TPS4580
Tivantinib MET Plus erlotinib Phase 2 complete
Twardowski 4523
TRC 105 Endoglin Plus bevacizumab Phase 2 negative
Dorff 4542
Targeted Immunotherapy
Tumor antigens released by tumor cells
Tumor antigens presented to T cells T cells are
activated and proliferate
T cells recognize tumor antigens
T cells kill tumor cells
The T-cell antitumor response
APC = antigen-presenting cell. Andersen MH, et al. J Invest Dermatol. 2006;126:32–41; Pardoll DM. Nat Rev Cancer. 2012;11:252–264; Mellman I, et al. Nature. 2011;480:480–489; Heemskerk B, et al. EMBO J. 2013;32:194–203; Boudreau JE, et al. Mol Ther. 2011;19:841–853; Janeway CA, et al. Immunobiology: The Immune System in Health and Disease. 6th ed. New York, NY: Garland Science; 2004.
1
4
2 3
5
Tumor cell
APC
Inactive T cell
Activated T cell
Activated T cell
Tumor cell
Tumor cell
Tumors use complex, overlapping mechanisms to evade and suppress the immune system
APC = antigen-presenting cell; MHC = major histocompatibility complex; TGF-ß = tumor growth factor-ß. Drake CG, et al. Adv Immunol. 2006;90:51–81; Vesely MD, et al. Annu Rev Immunol. 2011;29:235–271.
Inhibition of tumor antigen presentation
e.g. down regulation of MHC I
1 APC
Recruitment of immunosuppressive cell
types e.g. T-reg
4
Regulatory T cell
Secretion of immunosuppressive factors
e.g. TGF-ß
2
Tumor cell
Inhibition of attack by immune cells
e.g. disruption of T-cell checkpoint pathways
3
Inactive T cell
Regulating the T-cell immune response
T-cell responses are regulated through a complex balance of inhibitory (‘checkpoint’) and activating signals
Tumors can dysregulate checkpoint and activating pathways, and consequently the immune response
Targeting checkpoint and activating pathways is an evolving approach to cancer therapy, designed to promote an immune response
The image shows only a selection of the receptors/pathways involved. CD = cluster of differentiation; CTLA-4 = cytotoxic T-lymphocyte antigen-4; LAG-3 = lymphocyte-activation gene-3;
PD-1 = programmed cell death-1; TIM-3 = T-cell immunoglobulin domain and mucin domain-3. Adapted from Mellman I, et al. Nature. 2011;480:481–489; Pardoll DM. Nat Rev Cancer. 2012;12:252–264.
PD-1
CTLA-4
Inhibitory receptors
Activating receptors
TIM-3
LAG-3
Antagonistic (blocking) antibodies
Agonistic antibodies
T-cell stimulation
CD28
OX40
CD137
PD-1/PD-L1 Inhibitors Currently in Clinical Development Target Agent
Nivolumab
(MDX1106, BMS936558)
Class IgG4 fully human Ab
KD
3 nM
PD-1 PD-L1
Pembrolizumab (MK-3475) Pidilizumab (CT-011) AMP-224 BMS935559 (MDX-1105) MPDL3280A MEDI4736 MSB0010718C
IgG4 engineered humanized Ab IgG1 humanized Ab Fc-PD-L2 fusion protein IgG4 fully human Ab IgG1 engineered fully human Ab IgG1 engineered fully human Ab NA
29 pM - - - - - -
43
Study design
Previously treated mRCC
Stratification factors
Region MSKCC risk group
Number of prior anti-angiogenic therapies
Nivolumab 3 mg/kg intravenously
every two weeks
Everolimus 10 mg orally once daily
Ran
dom
ize
1:1
• Patients were treated until progression or intolerable toxicity occurred • Treatment beyond progression was permitted if drug was tolerated and
clinical benefit was noted MSKCC, Memorial Sloan-Kettering Cancer Center.
OS: Prior therapy
Nivolumab Everolimus
Favors
Subgroup
Nivolumab Events/patients
Everolimus Events/patients
Hazard ratio (95% CI)
Prior therapy Sunitinib Pazopanib
123/257 53/126
138/261 79/136
Months on first-line therapy <6 ≥6
61/110 122/300
81/130 134/281
Prior anti-angiogenic therapies 1 2
144/317 37/90
162/312 53/99
0 1 2
Targeted therapy sequencing in RCC
Novel treatment options with different mechanisms of action are needed
Sunitinib
Pazopanib
Everolimus
Axitinib
First-line Second-line Nivolumab
Cabozantinib
Lenvatinib?
Escudier B et al. Ann Oncol. 2014;25(suppl 3):iii49-iii56.
* Sunitinib is first option for non-clear cell RCC
*Temsirolimus is approved for poor risk pts
*
*
Current treatment landscape: anti-VEGF agents and mTOR inhibitors
2nd-
line
1s
t-lin
e
Months
Median OS
Sunitinib vs. IFN-α Motzer et al. JCO 2009
Pazopanib vs. sunitinib Motzer et al. NEJM 2013
Bev + IFN-α vs. IFN-α + placebo Escudier et al. JCO 2010
Pazopanib vs. placebo Sternberg et al. EJC 2013
Temsirolimus vs. IFN-α Hudes et al. NEJM 2007
Temsirolimus vs. sorafenib Hutson et al. JCO 2014
Sorafenib vs. placebo Escudier et al. JCO 2009
Everolimus vs. placebo Motzer et al. Cancer 2010
Axitinib vs. sorafenib Motzer et al. Lancet Oncol 2013
HR 0.82; P = 0.051
HR 0.91; P = 0.221
HR 0.91
HR 0.73; P = 0.008
HR 0.86; P = 0.129
HR 0.88; P = 0.146 HR 0.87; P = 0.162
HR 0.97; P = 0.374
HR 1.31; P = 0.010
Agent under investigation Comparator
¿ Que hemos aprendido en la última década de CCR?
• 1.- A clasificar histopatológicamente los pacientes.
• 2.- A agruparlos/clasificarlos por grupos de riesgo y OS.
• 3.- Son tumores proangiogénicos donde funcionan todos los fármacos antiangiogénicos
• 4.- La secuenciación de fármacos es el gold-estándar en la enfermedad avanzada.
• 5.- Un buen manejo de la toxicidad y comorbilidades de los pacientes es clave para su mejor OS
• 6.- La nueva Inmunoterapia abre nuevas líneas de investigación prometedoras en CCR
• 7.- Quedan muchas preguntas por resolver como la ausencia de biomarcadores, terapias mas eficaces en tumores no células claras y mejoras en calidad de vida.
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