Personalized Management of HCC - viemgansieuvi.vn · Personalized Management of HCC . Postgraduate...

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1 Personalized Management of HCC Postgraduate Course: Challenges in Management of Common Liver Diseases Josep M. Llovet, MD, FAASLD Professor of Medicine. Director, Liver Cancer Program, ISM at Mount Sinai, NYC. Professor of Research-ICREA. BCLC Group-IDIBAPS. Liver Unit . Hospital Clínic Barcelona. 526

Transcript of Personalized Management of HCC - viemgansieuvi.vn · Personalized Management of HCC . Postgraduate...

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Personalized Management of HCC

Postgraduate Course:

Challenges in Management of Common Liver Diseases

Josep M. Llovet, MD, FAASLDProfessor of Medicine. Director, Liver Cancer Program, ISM at Mount Sinai, NYC.

Professor of Research-ICREA. BCLC Group-IDIBAPS. Liver Unit . Hospital Clínic Barcelona.

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© 2016 AMERICAN ASSOCIATION FOR THE STUDY OF LIVER DISEASES

WWW.AASLD.ORG 2

Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

527

Case description

69- yr old man, with compensated HCV-cirrhosis

• 2012: Single HCC 5cm, no macrovascular invasion (MVI) or extrahepatic spread (EHS)

Child-Pugh A, ECOG 0, Bilirubin: 1 mg/dL and no portal hypertension

Segmental resection: R0, no satellites, microvascular invasion

• 2014: Multinodular HCC recurrence: 3 nodules (max: 4cm)

Child-Pugh A, ECOG 0, no MVI- EHS, AFP: 100 ng/mL

Chemoembolization (TACE x3): partial response

• 2016: Progression main HCC nodule : 6cm, satellites and branch portal vein thrombosis

Child-Pugh A, ECOG 1, Bilirubin 1.5 mg/dL, AFP: 600 ng/mL.

Treatment strategy?

a) TACE b) Sorafenib c) TARE (Y-90) d) Radiotherapy

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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EASL Guidelines. Management of HCC. 2001, 2012; EORTC 2012

AASLD guidelines. Management of HCC, 2005, 2011

BCLC staging system Scientific societies endorsing BCLC

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BCLC Staging and treatment schedule

Llovet JM et al. Nat Rev Dis Primers 2016

Unresectable HCC

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Median survival: Placebo 15.8m Seocalcitol 15.1m

p=0.76

Llovet et al, Hepatology 1998; Beaugrand M, et al. J Hepatol, 2005A.

Survival BCLC B stage (n=370)

Intermediate-advanced HCC

RCT seocalcitol vs placebo (n=746)

Median survival : Placebo 5.7m Seocalcitol 5.6m

27%

23% 10%

11%

p=0.37

Survival BCLC C stage (n=376)

Redefining “unresectable” HCC: NATURAL HISTORY -BCLC B and C

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BCLC Staging and treatment schedule

Llovet JM et al. Nat Rev Dis Primers 2016

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Evidence and recommendations for HCC therapies

EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012

534

Systemic therapies: sorafenib

• Sorafenib

Stratification:

* Macroscopic vascular

invasion (portal vein)

and/or extrahepatic spread

* ECOG PS

* Geographical region

Sorafenib

(n=299)

400 mg po bid

continuous

dosing

Ran

do

miz

ati

on

N=

602

Placebo

(n=303)

2 tablets po bid

continuous

dosing

Llovet JM et al, NEJM 2008;359:378-90 EASL-EORTC Guidelines , J Hep 2012. 535

BCLC Staging and treatment schedule

Llovet JM et al. Nat Rev Dis Primers 2016

Endorsed by AASLD, EASL, EORTC, ESMO

536

Phase III SHARP Trial Subgroup analysis: portal vein invasion

Bruix et al, J Hepatol 2012. 537

Alternative therapies for macrovascular invasion in HCC

• Restrospective studies

• Underpowered, selection bias

• Hypothesis generating

Author (n) Survival

Roayaie S ; Ann Surg Oncol 2013 165 13.1 mo

Surgical resection

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Alternative therapies for macrovascular invasion in HCC

Author Treatment (n) Survival

Xue , BMC Gastro 2013 TACE (160) Meta-analysis

Gorodeski, Eur Rad 2016 TACE (95) 5 mo

TACE-DEB (38) 3.3 mo

Zhu K, Radiology 2014 TACE+S (46) 13mo

TACE 6 mo

Memon K, J Hep 2013 Y-90 13 mo (Child A)

6 mo (Child B)

Nakazawa, BMC Gastro 2014 Sorafenib (40) 4.3 mo

Radiotherapy (57) 5.9mo

• Restrospective studies

• Underpowered, selection bias

• Hypothesis generating

Loco-regional therapies: TACE and TARE, Radiotherapy

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Radioembolization for portal vein invasion in HCC

Salem R et al, Hepatology 2013

• Hypothesis generating

Completed Completed Recruiting Completed

Prospective/retrospective studies

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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Landscape of mutations in HCC

Vogelstein et al, Science 2013

35-40

Zucman-Rossi and Llovet groups, Nat Genetics 2015

• Genome sequencing in HCC (n=250)

Undruggable mutations

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Llovet JM et al , Nat Rev Clin Oncol 2015

Landscape of mutations in HCC (meta-analysis, n= 928)

Untargetable drivers

Targetable drivers

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Signaling pathways (mut): • Telomerase maintenance: 60% • Cell cycle gene: 49% • Wnt-B-Catenin: 54% • Epigenetic modifier: 32% • Akt/mTOR: 51% • MAPK: 43%

Signaling pathways (other): • NOTCH: 30% • TGF-Beta: 17% • MET: 50% • IGF Signaling : 15% (IGF2 epi-driver)

Zucman-Rossi, Nat Genetics 2015 Villanueva, Gastrotenterology 2012; Coulouarn et al, Hepatology 2008

Molecular targets for HCC Signaling pathways: molecular targets for new therapies.

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Molecular classification of HCC

Zucman J, et al Gastroenterology 2015 545

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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Molecular alteration Clinical significance REMARK recommendations Status

Signatures from HCC

5-gene signature Poor survival OK 1,2 (3)

EpCAM signature Poor survival OK 1,2

Down-regulation miR-26a Poor survival OK 1,2

Signature from adjacent tissue

Poor-survival signature Poor survival OK 1,2 (3)

Modeling prognosis in HCC Gene signatures/ biomarkers with prognostic power

mRNA based (gene signatures)¶

Biomarkers AFP (200-400 ng/mL; Ang2, VEGF) Poor survival Ok 1,2 (3)

Level II-C

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Nault et al. Gastroenterology. 2013.

Outcome approach-Survival

Modeling Prognosis- molecular outcome in HCC

• 5-gene survival signature (HN1,RAN,RAMP3,CK19,TAF9) Training: 189, Validation : 125 External Validation: Western Cohort: 213 Asian Cohort: 221

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p<0.01

Gene signature-poor prognosis: # 186 genes

Gene Set Enrichment : 1. Inflammation 2. NF-KB

signaling 3. interferon-related immune response 4.

Oxidative stress and 5. Proliferative signals (IL6, EGF)

Training set (n=82)

Hoshida et al, NEJM 2008

Relevance of microenvironment Molecular prognosis of HCC

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Nault et al. Gastroenterology. 2013.

Outcome approach-Survival

Modeling Prognosis- molecular outcome in HCC

550

Modeling prognosis in HCC Gene signatures/ biomarkers with prognostic power

Llovet JM et al , Nat Rev Clin Oncol 2015

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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Phase III SHARP Trial Sorafenib vs placebo in advanced HCC

Stratification:

* Macroscopic vascular

invasion (portal vein)

and/or extrahepatic spread

* ECOG PS

* Geographical region

Sorafenib (n=299)

400 mg po bid

continuous dosing

Ran

do

miz

ati

on

N=

602

Placebo (n=303)

2 tablets po bid

continuous

dosing

Llovet JM et al, NEJM 2008;359:378-90

Hazard ratio (S/P): 0.69 (95% CI: 0.55, 0.87). P=0.00058*

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Phase III SHARP and AP Trials Predictors of response to sorafenib (n=827 pts)

Baseline Covariate

Number of patients Hazard Ratioa

(sorafenib/placebo)

Treatment

Interaction

Sorafenib Placebo HR (95% CI) P Value

EHS No

Yes

187

261

178

201

0.55 [0.42–0.72]

0.84 [0.67–1.05]

0.015

HCV No

Yes

303

111

265

88

0.81 [0.66–0.99]

0.47 [0.32–0.69]

0.035

Neutrophyl to

lymphocyte ratio

≤median

>median

238

207

192

184

0.59 [0.46–0.77]

0.84 [0.66–1.05]

0.0497

Bruix J, Hepatol Int 2016 (suppl 1).

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Variable

Multivariate Analysis

P-value HR

Macrovascular invasion 0.005

Extrahepatic spread 0.016 2.530

Baseline AFP 0.014 1.473

Baseline alkaline phosphatase 0.001 1.802

Baseline c-KIT 0.006 0.562

Baseline HGF 0.014 1.678

Sorafenib Cohort

Baseline AFP 0.008 1.599

Macroscopic vascular invasion <0.001 2.077

Baseline alkaline phosphatase 0.015 0.039

Baseline Ang2 0.002 1.629

Baseline VEGF 0.002 1.979

Placebo Cohort

Predictors of Survival All patients (multivariate analysis)

Llovet et al, CCR 2012.

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Predictors of response to sorafenib

Patients with high c-KIT showed a trend of better OS benefit from sorafenib (interaction P-value=0.081).

Predictors of survival: C-KIT Status

Llovet et al, CCR 2012.

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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Molecular therapies tested for HCC in Phase III (2016)

Adjuvant Prevent recurrences 1. Sorafenib vs placebo (STORM)*

2. Retinoids vs placebo*

Intermediate HCC Improve TACE 1. RF vs RF-Dox

2. TACE+/- sorafenib*

3. TACE +/- brivanib*

Advanced HCC First line: 1. Sorafenib + /- erlotinib*

2. Sorafenib vs brivanib*

3. Sorafenib vs sunitinib*

4. Sorafenib vs linifanib*

5. Sorafenib +/- Doxorubicin*

6. Sorafenib +/- Y90

7. Sorafenib vs lenvatinib

8. Sorafenib vs nivolumab

Second line: 1. Brivanib vs placebo*

2. Everolimus vs placebo*

3. Ramucirumab vs placebo*

4. Regorafenib vs placebo

5. Tivantinib vs placebo

6. Cabozantinib vs placebo

7. Pembrolizumab vs placebo

Targeted population Phase III comparison

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Why these RCT are negative in HCC?

1. Limited understanding of molecular drivers

2. Lack of translation of knowledge into trial design

3. Two diseases: HCC and cirrhosis

- Balance between efficacy and toxicity (sunitinib, linifanib)

- Difficult trial design:

Non-inferiority concept (Brivanib, linifanib)

Surrogate end-points of survival? TTP (contradictory data), ORR

4. Moving to phase III without clear signals. (Sunitinib, erlotinib)

5. Drugs are not powerful enough

(brivanib, linifanib, erlotinib, everolimus, ramucirumab, doxo).

Llovet JM et al, Clin Can Res 2014

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Strategies to overcome failures

1. Targeting all comers with more effective drugs

– Multikinase inhibitors: regorafenib, lenvatinib

– Immunotherapy: nivolumab

– Combination.

2. Selective targeting of drivers: precision medicine

– Oncogenic loops: FGF19, IGF2, CTNNB1

– Signaling pathways: TGF-Beta, MET, Akt/mTOR,

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Llovet JM et al, Nature Review Disease Primers 2015

Drug Phase Target(s) Trial enrichment Primary end point NCT

Antiangiogenic agents

Lenvatinib III VEGFR2/3 No OS NCT01761266

Ramucirumab III VEGFR2 αFP>400 OS NCT02435433

Regorafenib III VEGFR2/TIE2 No OS NCT01774344

Apatinib III VEGFR2 No OS NCT02329860

Axitinib II VEGFR/C-KIT/PDGFR No DCR NCT01273662

Tivozanib I-II VEGFR No PFS NCT01835223

TRC 105 + Sorafenib I-II Endoglin No MTD/TTP NCT01306058

Cell-cycle inhibitors and antiproliferative agents

Tivantinib III Tubulin inhibitor/MET MET+ OS NCT01755767

Cabozantinib III MET; VEGFR No OS NCT01908426

INC280 II MET MET pathway deregulation TTP NCT01737827

MSC2156119J I-II MET MET+ DLT/TTP NCT01988493

LY2875358 + Ramucirumab I-II MET/VEGFR2 No DLT/ORR NCT02082210

Galunisertib +/- Sorafenib II TGFβR1 No OS NCT02178358

Galunisertib + Nivolumab I-II TGFβR1/anti-PD-1 No MTD NCT02423343

Temsirolimus + Sorafenib II mTOR No TTP NCT01687673

Donafenib I-II RAF No DLT NCT02229071

FGF401 I-II FGFR4 FGFR4 and KLB+ expression DLT/TTP/ORR NCT02325739

TKM-080301 I-II PLK1 No MTD NCT02191878

BLU-554 I-II FGFR4 FGF19 amplification/overexpression MTD NCT02508467

Immune-modulators

Nivolumab II; III anti-PD-1 No ORR; OS

MEDI4736 + tremelimumab I-II anti-PD-L1/CTLA-4 No DLT NCT02519348

Miscellaneous

CF102 II Adenosine receptor A3 No OS NCT02128958

Enzalutamide II Androgen receptor No OS NCT02528643

LEE011 II CDK4/6 No PFS NCT02524119

BBI503 II Nanog No DCR NCT02232633

BBI608/503 + Sorafenib I-II STAT3/Nanog No DLT NCT02279719

DCR-MYC I-II MYC No DCR NCT02314052

Resminostat I-II HDAC No DLT NCT02400788

Phase I-III studies in HCC: targeting all comers

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SETTING N REGORAFENIB DOSE

EFFICACY SAFETY

2nd line 36 160 mg PO QD 21d on/7d off

DCR: 72% PR: 3% SD: 69%

Median TTP: 4.3 mo Median OS: 13.8 mo

All Grade/Grade >3 /Drug-related Aes:

HFSR: 53% 14%

Diarrhea: 53% 6%

Fatigue: 53% 17%

Hypothyroidism:42% 0%

Hypertension: 36% 3%

Bruix J, et al. Eur J Cancer 2013

Regorafenib: phase II study in 2n line

562

Phase III studies in HCC: Regorafenib 2nd line

Regorafenib 160 mg po once daily

3 weeks on / 1 week off

(4-week cycle)

(n=379)

Placebo (n=194)

• 152 centers in 21 countries in North and South America, Europe, Australia, Asia

• All patients received best supportive care

• Treat until progression, unacceptable toxicity, or withdrawal

• HCC patients with documented

radiological progression during

sorafenib treatment

• Stratified by:

− Geographic region (Asia vs ROW)

− Macrovascular invasion

− Extrahepatic disease

− ECOG PS (0 vs 1)

− AFP (<400 ng/mL vs ≥400 ng/mL)

N= 573

ROW, rest of the world; ECOG PS, Eastern Cooperative Oncology Group performance status; AFP, alpha-fetoprotein

R 2:1

Bruix J-RESORCE, WCGC 2016. 563

Phase III studies in HCC: Regorafenib 2nd line Regorafenib vs placebo

Pro

bab

ilit

y o

f S

urv

ival

(%)

Regorafenib

N=379

Placebo

N=194

Events 232 (61%) 140 (72%)

Censored 147 (39%) 54 (28%)

Median OS 10.6 months 7.8 months

HR 0.62 (95% CI: 0.50, 0.78)

P <0.001

• Overall survival • Time to Progression

Regorafenib

N=379

Placebo

N=194

Events 273 (72%) 173 (89%)

Censored 106 (28%) 21 (11%)

Median TTP 3.2 months 1.5 months

HR 0.44 (95% CI: 0.36, 0.55)

P <0.001

• Regorafenib

1. Positive results in terms of OS vs placebo in patients progressing to sorafenib

2. Magnitud of benefit is clinical significant: will become standard of care

Bruix J-RESORCE, WCGC 2016. 564

Nivolumab (anti-PD-1) in Phase I/II in HCC

El-Khoueriry al, ASCO 2015

Sangro, ASCO 2016

ORR OS n=42 19% 62%- 1yr n~200 16% 14 mo

Herbst et al, Nature, 2014

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Molecular classification of HCC

Zucman J et al, Gastroenterology 2015

Anti-TGF-Beta

AktmTOR/ MET inhibitors RAS inhibitors

Anti-CTNNB1 Anti-FGFR4

Anti-IGF2

566

Linking targets and therapies in HCC

Llovet JM et al. Nat Rev Dis Primers 2016

567

FGF19 is a molecular driver in HCC

Lo

g2 f

old

ch

an

ge

Chromosome 1 X

Am

plic

on fre

q.

FGF19 amplification: 7%

FGF19 gene amplification

FISH

FGF19 up-regulation

IHC

Sawey Cancer Cell 2011; Hagel Cancer Discovery 2015; Schulze Nature Genetics 2015; Totoki Nature Genetics 2015.

FGF19 RNA expression

Proof of concept trial

568

FGFR4 inhibitors in FGF19-positive PDX Models

Hagel M, et al. Cancer Discovery. 2015

FGF19 amplification FGF19 overexpression

Phase I-II: FGFR4 inhibitor assessing response in patients with amplification/overexpression FGF19

569

Tivantinib vs placebo in 2nd line: Phase II studies

• Tivantinib (n=71; OS= 6.6 mo) vs placebo (n=36; OS= 6.2 mo)

Santoro et al, Lancet Oncol 2013

• Subgroup analysis-Enrichment for c-MET +: Tivantinib 7.2mo vs placebo 3.8 mo

Phase III: tivantinib vs placebo in 2nd line in

MET+ patients

Biomarker-based Trial enrichment

570

Ramucirumab for advanced HCC: Phase III, 2nd line

Zhu et al, Lancet Oncol 2015

Phase III: ramucirumab vs placebo in 2nd line in

HCC-AFP>400 ng/mL

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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Questions & Answers (I) Q1- Personalized treatment for HCC

Defining tumor stage according to AASLD/ EASL Clinical Practice Guidelines

• BCLC staging system: defines prognostic stages and allocates the best treatment according to evidence

Defines standard of care

• Other staging systems( i.e Hong Kong): Describes treatment schedules according to practice

Defines standard of practice

Defining treatment for multinodular tumors with macrovascular invasion

• Sorafenib: standard of care according to level #1 evidence in AASLD, EASL-EORTC guidelines

• Other treatments (i.e TARE-Y90): have reported promising results in cohort studies (level #2 evidence) and thus require randomized studies prior of being adopted by Clinical Practice Guidelines

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Questions & Answers (II) Q2- Role of biomarkers

Defining biology and molecular classes

• Oncodrivers: Mutations of TERT promoter p53 , CTNNB1, ARID1 , Amplification VEGFA, FGF19

Impact: Few are targetable. Trial enrichment for oncogenes (i.e FGF19)/ signaling cascades (MET, TGF-B)

• Molecular classes: 1. Tumor profiling : a)Proliferation-TGF-B, b) Proliferation-progenitor, c)CTNNB1

2. Adjacent tissue profiling

Impact: Biologically meaningful, not yet translated into clinical setting

Predicting prognosis

• Prognosis: AFP > 200 or 400 ng/mL , 5-gene signature , 186 adjacent tissue signature.

Impact: So far used to define patients with poor outcome and for stratification of HCC trials

Predicting response to sorafenib

• Predictors: Sorafenib benefits all subgroup of patients. HCV-patients have better outcome than non-HCV

There are no biological markers predicting response to sorafenib

Impact: HCV can be considered for stratification of trials testing sorafenib

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Questions & Answers (III) Q3- New targeted therapies and precision medicine for HCC

1. Regorafenib: as only second line therapy in patients progressing to sorafenib

Impact: Pending FDA approval for clinical use

Will change CP Guidelines for management of HCC

2. Emerging molecular therapies for “all comers” :

Potent/non-toxic TKI: lenvatinib.

Alternative drugs: check-point inhibitors (nivolumab: pembrolizumab)

Impact: If positive might change standard of care (CP Guidelines)

3. Proof of concept and trial enrichment for

a) Oncogenic loops (i.e FGF19/FGFR4 )

b) Signaling cascades MET: tivantinib, VEGF/MET: cabozantinib

c) Biomarkers (AFP: ramucirumab)

Impact: If positive might become the first biomarker-driven standard of care in HCC

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Personalized management of HCC 1. Case description

2. Q1- Personalized treatment of HCC

3. Q2- Role of biomarkers

• Defining biology and molecular classes

• Predicting prognosis

• Predicting response to sorafenib

4. Q3- New target therapies: precision medicine for HCC

5. Question & Answer

6. Conclusion

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Conclusions & recommendations 1. Personalized management (case): as per AASLD-EASL Guidelines (evidence, standard of care)

Treatment 1st: sorafenib……alternative therapies (i.e Y90, lenvatinib) require level #1 evidence

Prognosis: median survival 8-9 mo; AFP >600 ng/mL biomarker predictor of poor outcome

2. Biomarkers:

a) Define molecular subclasses : proliferation, progenitor cell, Wnt-CTNNB1

b) Predict prognosis : 5-gene signature, 186-signature adjacent tissue, AFP

c) Predict better response to sorafenib: HCV

Waiting for translational trials to be incorporated in CP Guidelines

3. Precision medicine:

a) Sorafenib is the standarad of care for advanced HCC

b) Regorafenib will become the standard of care for patients progressing to sorafenib

c) Trials with proof-of-concept (FGF19) or trial enrichment (MET+, AFP+, etc..) are needed in HCC

If positive, they will incorporate biomarkers in the clinical decision-making

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