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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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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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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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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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Evidence and recommendations for HCC therapies
EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012
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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
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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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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
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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
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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
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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
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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
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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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