cpnm diagnóstico molecular: en busca de la diana …...cpnm diagnóstico molecular: en busca de la...
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CPNM Diagnóstico Molecular: en busca de la Diana Perdida
Problemas y alternativas
Carlos Camps. Panticosa 2014
“New Era of Personalized Medicine” portada en 1999 en The Wall Street Journal
15 años despues y > 3 Billones $ invertidos en estudios genomicos 2013
1
/2/
02/ z
n
xzP
2
KRAS as Prognostic Biomarkers for LUNG CANCER
Table 2 . KRAS mutations: correlation with Histology Table 3. KRAS mutations: correlation with Smoking Status
81.2 meses
23 meses
KRAS SCC ADC* Others Total p
WT 67 51 16 134
0.002 98.5% 79.7% 88.9% 89.3%
Mutated 1 13 2 16
1.5% 20.3% 11.1% 10.7%
Poster145
Madariaga, et al SEPAR 2014, Camps C ASCO 2013
KRAS Non Smoker
Former Smoker
Current Smoker
Total p
WT 13 54 67 134
0.007 Mutated
6 4 6 16
37.5% 25% 37.5% 100%
Terapia basada en dianas en Oncologia
The hope for the future
Individualized Medicine
Breast cancer
Prostate cancer
Lung cancer
Molecular diagnostics
Treatment A
Treatment B
Treatment C
Standard TX
Modified from American Association for Cancer Research
Nuevas mutaciones en el proceso de metastasis
Scott Valastyan and Robert A. Weinberg, Cell 2011, 147: 275-292
" Unless you can express your knowledge with numbers, your knowledge is meager and unsatisfactory." William Thompson. Lord Kelvin 1824-1907
Smithsonian Institution of Washington, 1857
Cuando y Como empezó esta historia en Ca de Pulmón ?
EGFR /2004
Dominio extracelular
Dominio Trans-
membrana
Dominio Tirosin Kinasa
Dominio Regulador
EGFR
Chr
omos
ome
7 C
rom
osom
a 7
Cell-cycle checkpoints (Hemmungseinrichtung: inhibitory mechanism) that would allow cell division only when a specific external stimulus is experienced by the cell.
The clonal origin of tumours
Tumour-suppressor genes (Teilungshemmende Chromosomen), the effects of which can be overcome by external signals, and which are physically lost in progressively growing tumours.
Oncogenes (Teilungsfoerdernde Chromosomen) that become amplified (im permanenten Übergewicht) during tumour development.
Tumour progression from benign to malignant, involving sequential changes of increased growth-stimulatory chromosomes & loss of growth-inhibitory chromosomes.
Cancer predisposition through inheritance of chromosomes (genes) that are less able to suppress malignancy.
Cancer predisposition through inheritance of genes that cause aberrant mitoses.
The role of wounding and inflammation in tumour promotion.
Loss of cell adhesion in metastasis.
Sensitivity of malignant cells to radiation therapy.
Prediciones de Boveri(1902)
Combined OS analysis: mutation categories
Presented by: James Chih-Hsin Yang ASCO 2014
1.0
0.8
0.6
0.4
0.2
0
Estim
ated
OS
prob
abilit
y
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51
Time (months)
1.0
0.8
0.6
0.4
0.2
0
Estim
ated
OS
prob
abilit
y Time (months)
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51
236 230 223 217 202 192 173 160 145 131 117 90 50 38 22 6 1 0
119 113 103 95 87 72 63 55 51 43 38 27 14 9 1 1 0 0
Afatinib
Chemo
No of patients
183 181 167 154 141 128 111 91 80 70 64 51 27 20 11 3 0 0
93 86 82 78 75 69 61 55 50 40 32 25 20 14 9 4 1 0
Afatinib
Chemo
No of patients
Del19 Afatinib n=236
Chemo n=119
Median, months 31.7 20.7
HR (95%CI), p-value
0.59 (0.45–0.77), p=0.0001
L858R Afatinib n=183
Chemo n=93
Median, months 22.1 26.9
HR (95%CI), p-value
1.25 (0.92–1.71), p=0.1600
Look to Mechanisms of EGFR TKI Acquired Resistance to Choose Systemic Therapies
T790M 63%
small cell + EGFR T790M
2%
small cell alone 1%
small cell+MET 1%
MET amplification alone
3%
MET + EGFR T790M 3%
Unknown 27%
Yu, Clin Cancer Res 2013
AZD9291 94%
Control
July 2009 January 2012
Mujer de 72 años ALK-Positivo tratada con Crizotinib
Desde publicacion EC pivotal NEJM 2010 hasta fijacion de precios España 2013
Acquired Resistance in ALK+ NSCLC
• ALK+ NSCLC is sensitive to crizotinib[1-3 ] – ORR: 60% – Median PFS: 8-10 mos
• Most patients with develop resistance to crizotinib[4,5] – Usually within 1-2 yrs – CNS relapses are common[6]
• Mechanisms of resistance are diverse[4,5]
– ALK resistance mutations – Alternative signaling pathways
Unknown
Bypass tracks EGFR MT KRAS MT
No ALK amp or mut
ALK amp
ALK mut ALK+
1. Camidge DR, et al. Lancet Oncol. 2012;13:1011-1019. 2. Kim DW, et al. ESMO 2012. Abstract 1230PD. 3. Show AT, et al. ESMO 2012. Abstract LBA1_PR. 3. Katayama R, et al. Sci Trans Med. 2012;4:120ra17. 4. Doebele RC, et al. Clin Cancer Res. 2012;18:1472-1482. 5. Takeda M, et al. J Thorac Oncol. 2013; 8:654-657.
Ou et al., Abstract # O16.07
Crizotinib Phase II trial in ROS1+ NSCLC Patients (1%)
Nuevas dianas en desarrollo Potential Treatment Model According to Genomic Drivers
AdvancedAdenocarcinoma
of lung
Genomic Profile
HER 2 mutation p
Afatinib + Herceptin
BRAF mutation GSK2118436
pC-MET
amplification Ficlatuzumab
ROS-1 LDK378
PI3K mutation BEZ235
KIF5B-RET Lenvatinib
La 1º Pregunta: Problemas:
La Complejidad y la Heterogeneidad
La teoría Darwiniana
Liquid
Nonsynonymous Somatic Mutations by Tumor Type
Vogelstein B, et al. Science. 2013;339:1546-1558.
Non
syno
nym
ous
Mut
atio
ns
per T
umor
(med
ian
± on
e qu
artil
e) 1500
1000
250 225
500
200 175 150 125 100
75 50 25
0
Col
orec
tal (
MSI
)
Lung
(SC
LC)
Lung
(NSC
LC)
Mel
anom
a
Esop
hage
al (E
SCC
)
Non
-Hod
gkin
’s ly
mph
oma
Col
orec
tal (
MSS
)
Hea
d an
d ne
ck
Esop
hage
al (E
AC)
Gas
tric
Endo
met
rial (
endo
met
riod)
Panc
reat
ic a
deno
carc
inom
a
Ova
rian
(hig
h-gr
ade
sero
us)
Pros
tate
Hep
atoc
ellu
lar
Glio
blas
tom
a
Brea
st
Endo
met
rial (
sero
us)
Lung
(nev
er s
mok
ed N
SCLC
)
Chr
onic
lym
phoc
ytic
leuk
emia
Acut
e m
yelo
id le
ukem
ia
Glio
blas
tom
a
Neu
robl
asto
ma
Acut
e ly
mph
obla
stic
leuk
emia
Med
ullo
blas
tom
a
Rha
bdoi
d
Mutagens Adult Solid Tumors Pediatric
ADJ CT in early stage NSCLC Where do we are? Where are we going?
Personalized treatment needed predictive biomarkers Pathologic factors Tumor heterogeneity and Host characteristics Microenvironment biomarkers immunotherapies ¿?
Rapid evolution of NGS and ↓ costs complete molecular profiling of each patient`s tumor is a realistic goal
Govidan, Cell 2012
SEGMENTACION
Burrell, Mcgranahan, Bartek and Swanton Nature 2013
Intertumour Heterogeneity Intratumour Heterogeneity Intercellular Heterogeneity
Review principles of intratumour heterogeneity learned from Renal Cancer Apply methods to study cancer evolution in Non-Small Cell Lung Cancer
Charlie Swanton, Sidney 2013
Intratumoral EGFR Mutational Heterogeneity Hua Bay et al, PLoS One. 2013; 8(2): e54170
1. Cancer Stem Cell (or like) – only few founders with tumorgenic potential
2. Therapeutic importance – target the few
3. BUT, although most evidence supports CSC - we don’t really know
Charlie Swanton, Sidney 2013
RELACIÓN FILOGENÉTICA DE LAS DISTINTAS REGIONES TUMORALES
•La evolución del tumor no es lineal, sino ramificada. •La longitud de ramificaciones es proporcional al nº de genes con mutaciones •Las mutaciones “driver ” son adquiridas en las ramificaciones. •En los tumores “convergencia fenotípica”: diferentes regiones del tumor tienen distintas mutaciones en los mismos genes.
… en otras palabras
NO ES ASI ES ASI
Una biopsia simple puede mostrar un máximo 50% de todas las mutaciones . Una biopsia no es representativa de un tumor .
Heterogeneidad T vs M
Bulletin Cancer 2013, S Vignot and JC Soria
Las mutaciones son dinámicas y los tumores heterogéneos y plásticos
Clonal Evolution
Peter C. Nowell. The Clonal Evolution of Tumor Cell Populations. Science (1976). Douglas Hanahan & Robert A. Weinberg. Hallmarks of Cancer: The Next Generation. Cell (2011). Felipe De Sousa E Melo. Cancer heterogeneity - a multifaceted view. EMBO report (2013).
1. Genetic disease (of the aged)
2. Evolving « system » (time &
space).
3. Heterogeneity !
Clonal Evolution (stepwise acquisition of mutations)
Epigenetics (DNA methylation, histone deacetylation )
Interaction (cell-cell, micro-enviroment)
4. Metabolism (almost) everywhere
27
NEW BIOMARKERS FOR LUNG CANCER: A METABOLOMIC APPROACH
Ayudas • Mutua Madrileña • AICR 2014 Camps C ASCO 2014
Multivariate modeling resulting from the analysis of serum 1H-NMR spectra.: (A) control individuals (red dots) vs early and advanced stage NSCLC patients (green and blue dots); (B) control individuals (red dots) vs early stage NSCLC patients (green dots); (C) control individuals (red dots) vs advanced stage NSCLC patients (blue dots) and (D) early stage NSCLC patients (green dots) vs advanced stage NSCLC patients (blue dots).
A B
C D
Inmunidad Uso M et al, PASCO 2014
PFS
Markers Median
(months) p-value
CTLA4 (≤ median vs > median)
19.23 vs 81.23
0.008
PD1 (≤ median vs > median)
19.13 vs 49.30
0.048
PDL1 (≤ median vs > median)
19.23 vs 66.96
0.034
Combined Checkpoints (Other combinations vs PD1high PDL1high)
19.23 vs NR 0.008 (0.048*)
81.2 m 22.1
m 25.6 m
NR NR
37.9 m miR-
188-5p miR-196b
miR-21
Gallach et al PASCO 2014
Existen otra formas de analizar el tumor?
CTCs
Cell free DNA
MA
TRIX
Serum Plasma (EDTA)
Proteins
Metabolites
En busca de las dianas Las Alternativas
Existen Modelos Organizativos de Éxito?
Principios rectores para construir estrategias en Genómica del Cáncer: Medicina Genómica del Cancer
Principio #1: Las Vías moleculares implicadas en la supervivencia y la progresión tumoral son activadas por alteraciones genéticas.
Garraway, J. Clin. Oncol., 2013
Principio #1: Las Vías moleculares implicadas en la supervivencia y la progresión tumoral son activadas por alteraciones genéticas. . Principio #2: Los Agentes anticancerígenos dirigidos a muchas vías oncogénicas podemos usarlos en ensayos clínicos
Garraway, J. Clin. Oncol., 2013
Principios rectores para construir estrategias en Genómica del Cáncer: Medicina Genómica del Cancer
Principio #1: Las Vías moleculares implicadas en la supervivencia y la progresión tumoral son activadas por alteraciones genéticas Principio #2: Los Agentes anticancerígenos dirigidos a muchas vías oncogénicas podemos usarlos en ensayos clínicos Principio #3: Las tecnologías genómicas permiten utilizar el perfil genómico en el ámbito clínico.
Principios rectores para construir estrategias en Genómica del Cáncer: Medicina Genómica del Cancer
Solomon, Sidney 2013
EL TIEMPO NECESARIO PARA TOMAR DECISIONES
COSMIC. Nucleic Acids Research, 2011, Vol. 39, Database issue
somatic mutation content of cell line NCI-H209. Concentric rings summarize the data on different types of mutation. From the inside out, the core displays the structural rearrangements; intrachromosomal are in green, interchromosomal in purple. The next ring out shows the chromosomal copy number in histogram form, with inner red patches indicating regions of LOH. Further out, several rings of single base coding substitutions are shown (black tiles show splice site mutations, red stop-gained, purple non synonymous and grey synonymous changes).
Describes over 136 000 coding mutations in almost 542 000 tumour samples; 26% have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs (19 new cancer genes and 30 new fusion pairs this year) and this number is continually increasing.
LCMC: frecuency of oncogenic drivers 83 specimens with all 10 drivers assesed
Ben Solomon, Sidney 2013
• Worldwide Innovative Networking • Initiated By MDACC and IGR
Only 50 % cured Late diagnosis Therapeutic failure
GAP
WIN
WORLDWIDE INNOVATIVE NETWORKING IN CANCER PERSONALIZED MEDICINE
The WIN organization www.winconsortium.org
Biomarcadores. Diferente implementación
Plataformas en España 2014 • PLATAFORMA 1DENTIFY (>22.000 muestras)
– H Doce de Octubre (Madrid) – H General de Valencia – H Virgen del Rocío (Sevilla) – Complejo Hospital Santiago – Pangaea Biotech (Barcelona) – Clinica Univ Navarra – H Valle de Hebron ( Barcelona) – H Germans i Pujol (Badalona) – H Joan XXIII ( Tarragona)
• PLATAFORMA DETERMINA RAS ( > 24.000) – Hospital del Mar (Barcelona) – Hospital Clínico San Carlos
(Madrid) – Hospital Universitario de Canarias
(Tenerife) – Fundación Jiménez Díaz, (Madrid) – Hospital Valle de Hebron – Hospital General de Valencia – Hospital Carlos Haya (Málaga)
Una red de equipos españoles trabajando coordinadamente en medicina personalizada?
Porque No?
Preguntas • ¿Qué perfiles mutacionales serán los más
adecuados para impulsar la medicina genómica? • ¿Qué arbol de decisiones puede hacer los datos
genómicos accesibles a los oncólogos? • ¿Qué diseños de ECs serán óptimos para analizar
la utilidad de la genómica en tumores? • ¿ Cómo van los oncólogos y los pacientes asumir
las cargas de la genómica a gran escala
Cancer Pulmón
Sexta Pregunta: la estrategia del “ME TOO” en Cancer es razonable?
Genetech Merck Novartis Eli Lilly Boeringher
Farmaceuticas + Academia + Investigadores
Tony Mok, Sidney 2013
Necesitamos un esfuerzo Global para evitar el “Me
Too”
51
Rafael Sirera
Jerónimo Forteza María Campos Segura Rut Lucas
LAB. ONCOLOGIA MOLECULAR Eloisa Jantus Lewintre
Silvia Calabuig Sandra Gallach
Marta Usó E. Sanmartin Eva Escorihuela
INVESTIGACION CLINICA
Belén Vazquez Vicente Castellano
Marta Aguiló
SERVICIO DE ONCOLOGIA Carlos Camps
Alfonso Berrocal Ana Blasco
Ma. José Safont Cristina Caballero Ma. José Godes
Vega Iranzo
SERVICIO DE CIRUGIA TORACICA Ricardo Guijarro Antonio Arnau
Santiago Figueroa Enrique Pastor
UNC F. Innocenti UCSF Trever Bivona
Antonio Pineda Rosa Farràs