utilidad de la biopsia líquida en cáncer de próstata · utilidad de la biopsia líquida en...

Utilidad de la biopsia líquida encáncer de próstata

Utilidad de la biopsia líquida encáncer de próstataEnrique González Billalabeitia

Servicio de Hematología y Oncología MédicaHospital G.U. Morales Meseguer

MurciaIX Reunión Nacional Cáncer de próstata, Cáncer renal y

cáncer de Vejiga.Mesa II. Cáncer de Próstata I

Guadalajara, 16 de Junio de 2017

Genetic evolution in Prostate Cancer

Rising PSANo visiblemetastasis

MetastaticDisease

InvasivediseaseInvasivedisease

Pre-invasivedisease(PIN)

No diseaseNo disease

Preventionof the disease

Prevention ofinvasion

Local treatment(RP or RT) orobservation(only selected

“Prevention” ofevident metastatic

disease

Systemictreatment

(ADT, HT, CT)

InflammationOxidative Stress

Telomere shortening

Senescence Castrationresistance

Myc TMPRSS2-ERGPTEN

inactivation

ERK/MAPK activationP53 inactivationRb inactivation

EZH2,P53, Rb inactivation

Lessons from TCGAMolecular subtypes based on driving gene

Focusing on advanced disease…

Rising PSANo visiblemetastasis

MetastaticDisease

InvasivediseaseInvasivedisease

Pre-invasivedisease(PIN)

No diseaseNo disease

Preventionof the disease

Prevention ofinvasion

Local treatment(RP or RT) orobservation(only selected

“Prevention” ofevident metastatic

disease

Systemictreatment

(ADT, HT, CT)

InflammationOxidative Stress

Telomere shortening

Senescence Castrationresistance

Myc TMPRSS2-ERGPTEN

inactivation

ERK/MAPK activationP53 inactivationRb inactivation

EZH2,P53, Rb inactivation

Lessons from Advanced disease

Robinson, D. et al. Cell 161, 1215–1228 (2015).

Summary of changes in key molecular eventsbetween Primary localized and mCRPC

Neuroendocrine PCa is derived fromdivergent differentiation

Beltran H. Nat Med 2016Dardene E & Beltran H. Cancer Cell 2016

Liquid biopsy as a reliable source forpersonalized therapies

Wyatt AW and Gleave ME. EMBO Mol Med 2015; 7:878-894

CTC study methods

CTC detection (>4) by CellSearch hasprognostic significance

Danila D. Clin Cancer Res 2007Olmos D. Ann Oncol 2008

CTC response is associated with goodprognosis

Olmos D. Ann Oncol 2008

Detection of any CTC by CellSearchmight be a better meassure

Prognostic significanceProportion of Eligible Patients Per Endpoint

Adapted form Glenn Heller at 2017 ASCO Annual Meeting

wC Idex: 0.83 wCI: 0.65

Basal CTC detection by AdnaTest isassociated with an adverse outcome

00 6 9 123Ra

Time (months)

00 6 9 123

Time (months)

00 6 9 123Ra

Time (months)

CTC yes vs no: median, 7.59 m versus NR,HR, 3.67; 95% CI 1.90-7.10; P < 0.001

median, 12.9 m versus NR;HR, 7.61; 95% CI, 2.80-20.64; P < 0.001

medians NR,HR, 9.51; 95% CI, 1.11-81.52; P = 0.0398

PREMIERE study. ASCO 2017

AR-V7 is associated with resistance tonovel antiandrogens

Antonarakis E. N Engl J Med 2014

AR-V7 has been associated withresistant in pre-treated mCRPC

Antonarakis E. N Engl J Med 2014Scher . JAMA Oncol 2016Antonarakis E. J Clin Oncol 2017

CTC by Epic Science technology is alsoassociated with outcome

Scher J. JAMA Oncol 2016

AR-V7 in CTCs in the PREMIERE trial

AR-V7 positive

AR-V7 negative

No CTCs

AR-V7 positive

AR-V7 negative

No CTCs

63 57 45 28 13 1 0

28 18 15 11 5 0 0

5 2 1 0 0 0 0

63 61 53 35 17 3 0

28 22 19 14 8 2 0

5 4 2 0 0 0 0

0 3 6 9 12 15 18

Months

0 3 6 9 12 15 18

Months

20 AR-V7 positive

No. at Risk

No CTCs

AR-V7 negative

AR-V7 positive

No. at Risk

No CTCs

AR-V7 negative

AR-V7 positive

Unpublished

HR = 1.80, 95%CI: 0. 51-6.31 HR =1.88, 95%CI: 0.51-6.87

Treatment response by AR-V7 statusA

AR-V7 negativeAR-V7 positive No CTCs

CTC positive, AR-V7non available

-100 Patie

No CTCs

AR-V7 positiveAR-V7 negative

CTC positive, AR-V7non available

0 3 6 9 12 15 18Months

(n=98) (n=98) (n=39)

Early Progression Late Progression

CTC-positiveAR-V7 positive

(n=20) (n=19)

P= 0,04

AR-V7 evolution during treatment

Months

AR-V7 positive: Routine monitoring; PSA progression; Radiographic progressionAR-V7 negative: Routine monitoring; PSA progressionAR-V7 non available: PSA progression

On-going response

70 55 36 20 4 0

17 5 2 1 0 0

8 0 0 0 0 0

70 61 44 26 8 0

17 9 3 2 0 0

8 3 0 0 0 0

3 6 9 12 15 18Months

100A B

3 6 9 12 15 18

Months

AR-V7 positive

AR-V7 negative

No CTCs

AR-V7 positive

AR-V7 negative

No CTCs

No. at RiskNo CTCsAR-V7 negativeAR-V7 positive

HR = 3. 73, 95%CI: 1. 44 -9.69; p=0.007 HR= 2.49, 95%CI: 0.69-8.99; p=0.16

AR-V7 at 12 weeks of treatment

Months

3 6 9 12 15 18

No CTCsAR-V7 positiveAR-V7 negativeCTC positive, AR-V7non available

Unpublished

Whole exome sequencing of CTCsprovides a window into metastatic PCa

Lohr et al. Nat Biotech 2014

Dynamic evolution of PSA & PSMAduring ADT treatment

Miyamoto DT. Cancer Discovery 2012

Switch to PSMA expression isassociated with castration resistance

Miyamoto DT. Cancer Discovery 2012

Plasma DNA study is clinically relevant

Wyatt et al, JAMA Onc 2016

DNA tumor fraction is clinically relevant• CtDNA fraction correlates with worse evolution

Median ctDNA fraction = 0.181 Romanel, Gasi Tandefelt et al. Sci Transl Med 2015, 312re10

Multiple Digital-droplet PCR (ddPCR)

Correlation between ddPCR y la NGSfor AR gain

AR aberrations are associated withadverse outcome

OR: 4.7; 95% CI, 1.17-19.17; P=0.035

OR: 5.0; 95% CI, 1.70-14.91; P=0.003

Condetuda V & Grande E. Annals of Oncology 2017

HR:3.98; 95% CI, 1.74-9.10; P <0.001 HR, 3.81; 95% CI, 2.28-6.37; P <0.001

HR, 2.18; 95% CI, 1.08-4.39; P=0.03 HR, 1.95; 95% CI 1.23-3.11; P=0.01

Patients with AR gain were less likely to have a ≥50%decline in PSA

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

AR Normal

Number at risk

AR Gain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

AR Normal

Number at risk

AR Gain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

AR Normal

Number at risk

AR Gain

ARNormal

ARGain

FIGURE 2

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

AR Normal

Number at risk

AR Gain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

AR Normal

Number at risk

AR Gain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

AR Normal

Number at risk

AR Gain

ARNormal

ARGain

FIGURE 2

PSA decline ≥ 50% AR gain vs normal: OR, 4.93; 95% CI, 1.30-18.75; P = 0.025

Plasma AR status is associated with worse outcome

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

AR Normal

Number at risk

AR Gain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

AR Normal

Number at risk

AR Gain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

AR Normal

Number at risk

AR Gain

ARNormal

ARGain

FIGURE 2

2a. 2b.

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

AR Normal

Number at risk

AR Gain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

AR Normal

Number at risk

AR Gain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

AR Normal

Number at risk

AR Gain

ARNormal

ARGain

FIGURE 2

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

ARNormal

Number at risk

ARGain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

ARNormal

Number at risk

ARGain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

ARNormal

Number at risk

ARGain

ARNormal

ARGain

FIGURE 2

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

AR Normal

Number at risk

AR Gain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

AR Normal

Number at risk

AR Gain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

AR Normal

Number at risk

AR Gain

ARNormal

ARGain

FIGURE 2

2a. 2b.

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

AR Normal

Number at risk

AR Gain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

AR Normal

Number at risk

AR Gain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

AR Normal

Number at risk

AR Gain

ARNormal

ARGain

FIGURE 2

0 3 6 9 120

Months

0 3 6 9 120

Months

0 3 6 9 120

Months

ARNormalARGain

83 82(1) 59(18) 38(6) 22(2)11 9(2) 3(6) 1(0) 0(0)

ARNormal

Number at risk

ARGain83 79(3) 70(4) 48(5) 29(1)11 9(2) 4(5) 2(1) 0(0)

ARNormal

Number at risk

ARGain

83 81(1) 76(0) 55(1) 32(1)11 11(0) 8(2) 4(1) 0(0)

ARNormal

Number at risk

ARGain

ARNormal

ARGain

FIGURE 2

Median sPFS: 3.60 versus 15.5 monthsHR, 4.33; 95% CI 1.94-9.68; P < 0.001

Median rPFS: 3.90 months versus not reachedHR, 8.06; 95% CI, 3.26-19.93; P < 0.001

Median OS: medians not reachedHR, 11.08; 95% CI, 2.16-56.95; P = 0.004

Multiple Genomic markers Correlatewith TTP

Adapted from Kim Chi at 2017 ASCO Annual Meeting

Includes patients without ctDNA. ** Mutation, deletion or rearrangement. *** includes trial arm, presence of quantifablectDNA and clinical prognostic factors (LDH, ALP, Visceral Mets, ECOG PS).

BRCA2/ATM

Presented By Kim Chi at 2017 ASCO Annual Meeting

• Truncating mutations or rearrangements (9.2%):Somatic 5.2% (6/115) and germline 4% (8/202)

• Non-truncating monoallelic mutations notassociated with TTP

Truncating mutations, rearrangements and deletions in56.5% (65/115)81% were early progressors (12 w)

ctDNA can be useful to identifyadquired mechanisms of resistance

Goodhal, Cancer Discovery 2017

ctDNA at relapse in the ToPARP studySubclonal aberrations reverting alterations in BRCA2 and PALB2are shown

Sub-clonal evolution and cross-metastaticseeding is observed in response to therapy

Hong M. Nat Comm 2015

Tumor Biopsy CTCs cfDNAGenomics High Low ModerateGeneexpression

High Moderate -

Protein High High -

The best technique?

Adapted from Joshua Lang presentation at 2017 ASCO Annual Meeting

Protein High High -

Heterogeneity High Moderate Moderate

Source High Moderate -

depends on what you are looking for?

Conclusion• CTCs are useful biomarkers

– Detection is associated with adverse prognosis.– CTC response can be an intermediate outcome for clinical

trials– Molecular characterization can be informative

• AR-V7 is prognostic• AR-V7 is associated with early resistance to

enzalutamide/abiraterone• ctDNA study captures tumor heterogeneity

– Is prognostic– ctDNA aberrations associate with adverse outcome

• AR-gain• Others: P53, RB,

• CTCs are useful biomarkers– Detection is associated with adverse prognosis.– CTC response can be an intermediate outcome for clinical

trials– Molecular characterization can be informative

• AR-V7 is prognostic• AR-V7 is associated with early resistance to

enzalutamide/abiraterone• ctDNA study captures tumor heterogeneity

– Is prognostic– ctDNA aberrations associate with adverse outcome

• AR-gain• Others: P53, RB,

Conclusion

• Further research is needed• We can anticipate that it will be key for

personalized therapy• Biomarkers qualification process

– Parallel to drug approval– Capture tumor dynamics

• Different clinical scenarios

• Further research is needed• We can anticipate that it will be key for

personalized therapy• Biomarkers qualification process

– Parallel to drug approval– Capture tumor dynamics

• Different clinical scenarios

AcknowledgmentsPREMIERE team:Enrique GrandeMaría Piedad Fernández PérezAlbert FontSergio Vázquez EstévezAránzazu González del AlbaBegoña MelladoOvidio Fernández CalvoMaría José Méndez-VidalMiguel Angel ClimentIgnacio DuranEnrique GallardoAngel RodríguezCarmen SantanderM Isabel SáezJavier PuenteTeresa AlonsoJulián TudelaAlberto MartínezDaniel CastellanoEnrique González Billalabeitia

Morales MeseseguerLab:Francisco Ayala de la PeñaHelena García MartínezMaría Piedad Fernández PérezJulián TudelaAlberto MartínezEnrique González Billalabeitia

Attard`s Lab:Gerhardt AttardDaniel WetterskogAnuradha JayaramAnna Wingate

Paolo CremaschiAnjuiKarolina NowakoskaAnjui Wu

PREMIERE team:Enrique GrandeMaría Piedad Fernández PérezAlbert FontSergio Vázquez EstévezAránzazu González del AlbaBegoña MelladoOvidio Fernández CalvoMaría José Méndez-VidalMiguel Angel ClimentIgnacio DuranEnrique GallardoAngel RodríguezCarmen SantanderM Isabel SáezJavier PuenteTeresa AlonsoJulián TudelaAlberto MartínezDaniel CastellanoEnrique González Billalabeitia

IRST team (Meldola)Ugo di GiorgiVinzenca Conteduca

Samantha Sanvi

Johns HopkinsEmmanuel AntonarakisJun Luo

AR Genomic Structural Rearrangements

Presented By Kim Chi at 2017 ASCO Annual Meeting

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