ONCOPROMESAS VS ONCOSAURIOSoncopromesas-oncosaurios.com/wp-content/uploads/... · MERKEL CELLS AND...

Coordinador Científico: Dr. Fernando Rivera Hospital Universitario Marqués de Valdecilla, Santander

Organizado por: Fundación para el progreso de la oncología en Cantabria, FUPOCAN

Carcinoma de Merkel abordaje molecular e implicaciones terapéuticas

ONCOPROMESAS VS ONCOSAURIOS 12, 13 Y 14 DE JULIO 2017 · SANTANDER

GRAN HOTEL SARDINERO

Pza. Italia,1· Santander

Asimilando los progresos en Oncología

José Pedro Vaqué Santander

MOLECULAR CHARACTERIZATION -MUTATIONAL PROFILING -OTHER MARKERS

GENERALISTIC THERAPIES

-SAME CONSIDERATION FOR PATIENTS, CANCERS AND CANCER CELLS-

TARGETED THERAPY IMATINIB CML HERCEPTIN BREAST CANCER CRIZOTINIB LUNG CANCER VEMURAFENIB ADVANCED MELANOMA

• CURE • INCREASES O. SURVIVAL • BETTER QUALITY OF LIFE

DISEASE MARKERS: -BRC-ABL -HER2 -BRAF

PERSONALIZED THERAPY • INDIVIDUAL MOLECULAR PROFILING • SPECIFIC MOLECULAR MARKERS • ADVANCED CANCER CASES WITH LIMITED TREATMENT OPTIONS

? ?

?

CHANGING OUR ABILITY TO DIAGNOSE AND TREAT CANCER

MERKEL CELL CARCINOMA ADVANCED MELANOMA CUTANEOUS T-CELL LYMPHOMA HEPATOCELLULAR CARCINOMA

-Relevant questions (clinical practice). -Patient selection/Management/Follow-up. -Sample collection, organization, characterization.

-Sample processing -Data generation and validation -Biological interpretation -Hypothesis/Preclinical models

-Translation into: Novel diagnostic tools Novel therapy options Clinical trials for personalize medicine??

1) SUPPORT DIAGNOSTICS 2) GUIDE THERAPY

PATIENT

CLINICIANS

TRANSLATIONAL RESEARCH PROJECTS

GREAT OPORTUNITY!

BASIC RESEARCHERS

ORGANIZED WORKFLOW FOR TRASLATIONAL PROJECTS

MERKEL CELLS AND MERKEL CELL CARCINOMA

▪ Neuroendocrine and thought to originate from the malignant transformation

of Merkel Cells.

▪ Infrequent, but with a rising incidence (0,2-0,8/100000 h)

▪ Local and distal metastasis are frequent at the time of diagnosis.

▪ Aggressive, with a high mortality rate (40%, exceeds melanoma)

▪ It affects especially aged and immunodepressed patients.

▪ From a mechanistic perspective Merkel cell carcinoma (MCC) is a poorly

studied cancer type

Diagnostic of MCCs can be difficult from other NET tumors:

Small Cell Lung Cancer (SCLC): CK20 (- ; 90% + in MCC), CK12(-), TTF-1 (+) (Pulitzer MP et al. Advances in Anatomic Pathology, 2009)

SCLC shares with MCC histopathological characteristics and aggressive clinical courses. (Schmidt U et al. The American Journal of Dermatopathology, 1998)

MERKEL CELL CARCINOMA: SOME RELEVANT FEATURES

MCCs can be divided into:

A) MCPyV+ tumors: With low mutational indexes.

B) MCPyV- tumors: With high mutational indexes with a UV signature (like melanoma)

-Disease markers have not provided significant differences in survival so far, except for TP53 in early

stages, MCPyV-negative expression or activated CREB (this presentation and Gonzalez-Vela C.) (Harms PW. et al. Can. Research, 2015)

(Wong QW. et al. Can. Research, 2015)

(Goh G. et al. Oncotarget, 2016)

(Moshiri AS. et al JID 2017)

(González-Vela C., Curiel-Olmo S. et al JID 2017)

MERKEL CELL CARCINOMA: SPECIFIC THERAPIES

Anti-PD1 treatment using Pembrolizumab has shown promising results in MCC with a PFS at 6

months of 67% of the patients (N= 24). (Nghiam PT et al. New England Journal of Medicine, 2016)

Anti-PD-L1 treatment using Avelumab has shown promising results in MCC with 28/88 patients

achieving an objective response (31.2% with CR or PR). Responses are durable. (Kaufman HL et al. Lancet Oncology, 2016)

Current treatment of MCC lacks targeted therapy or effective molecular therapies. Other

therapies like chemotherapy or radiotherapy are also low efficient in advanced stages (Schmidt U et al. The American Journal of Dermatopathology, 1998)

Ribas A. N Engl J Med. 2012;366:2517-2519.

THERE IS SCARCE KNOWLEDGE OF THE MOLECULAR MECHANISMS DRIVING THIS DISEASE

Integrated in the genome of 66 % - 80 % of MCC cases (Feng H et al. Science, 2008)

Codifies 3 antigens that are presumably required for

survival and proliferation of MCC:

1. Large T antigen (LT): RB

2. Small T antigen(ST) : Can promote

tumorugenesis in vivo

3. 57KDa antigen

(Shuda M et al. The Journal of Clinical Investigation, 2011)

(Verhaegen ME. Et al Cancer Research, 2017)

Viral antigens can bind tumor suppressor proteins

including RB. Other activities (i.e. TP53) are still

unveiled (DeCaprio JA et al. Cell, 1988)

Clonal integration of Merkel Polyomavirus (MCPyV) in Merkel cells

MERKEL CELL CARCINOMA: MOLECULAR PATHOGENESIS

The origin of MCC is still under discussion:

1. Merkel Cells

2. Epithelial pluripotent skin cells

(Mc Cardle et al. Curr. Probl. Cancer, 2010)

ETIOLOGY OF MERKEL CELL CARCINOMA

81 % of primary tumors occur on

sun-exposed skin. (Heath et al. 2008)

Caucasians have the greatest risk . (Heath et al. 2008)

UV signature. (Goh et al. 2015, Harms et al. 2015)

Found in 50 - 90 % of MCC tumors. (Feng et al. 2008, Kassem et al. 2008)

Immunodepressed people have

the highest risk. (Sarnaik et al. 2010)

MCPyV

MERKEL CELL POLYOMAVIRUS (MCPyV): UV RADIATION:

CANCER HETEROGENEITY (MUTATIONAL INDEX)

(Alexandrov, L.B. et al. Nature, 2013)

Prevalencia de mutaciones en diferentes tipos de cancer humano

MERKEL CELL CARCINOMA

MCPyV+ 0,7 muts/Mb

MCPyV- >20 muts/Mb

WHOLE EXOME SEQUENCING OF 15 MCC CASES

PATIENT SEX AGELESION

LOCALIZ.STAGE MCPyV

SAMPLE

TYPE

C>T

DIPYRIM

IDINE

% C>T

DIPYRIM

IDINE

CC>TT % CC>TT

1 M 83 Leg IIIA Negative FF 1875 83,71 6 0,27

2 M 94 Ear IV Negative FFPE 1562 79,17 16 0,81

3 M 74 Nose IA Negative FFPE 296 70,14 3 0,71

4 M 81 Face IIA Negative FF 1875 75,88 12 0,49

5 F 78 Face IV Negative FF 1995 75,45 16 0,61

6 F 92 Leg IV Negative FF 1306 72,72 8 0,45

7 F 75 Face IIA Negative FFPE 2562 70,31 11 0,30

8 F 80 Leg IIIA Positive FF 11 37,93 0 0,00

9 M 72 Arm IIIA Positive FFPE 143 33,57 0 0,00

10 F 88 Thigh IIA Positive FF 12 21,05 0 0,00

11 M 86 Leg IIIB Positive FF 17 26,98 0 0,00

12 F 80 Face IV Positive FF 9 36,00 0 0,00

13 M 69 Lip IV Negative FFPE 71 21,91 0 0,00

14 F 80 Face IIA Positive FF 6 16,22 0 0,00

15 F 81 Leg IIB Positive FF 8 17,02 0 0,00

MCPyV-: High mutational loads with a UV signature (% C>T at dipyrimidine sites)

MCPyV+: Low mutational loads

González-Vela C*,Curiel-Olmo S* et al. JID 2017

GENETIC CHARACTERISTICS OF MCC TUMORS: TOTAL NUMBER OF SNVs/CASE

MCPyV-: High mutational loads (average SNVs=1939) with a UV signature (% C>T at dipyrimidine sites)

MCPyV+: Low mutational loads (average SNVs=73)


GENETIC CHARACTERISTICS OF MCC TUMORS: U.V. SIGNATURE VS.MCPyV

MCPyV-: High mutational loads (average SNVs=1939) with a UV signature (% C>T at dipyrimidine sites)

MCPyV+: Low mutational loads (average SNVs=73)


SIGNIFICANTLY MUTATED GENES FOUND BY ONCODRIVE.

A tool designed to uncover significantly altered OncodriveFM: » driver genes or gene modules » pathways & biological processes

GENE P VALUE Q VALUE FUNTIONS MECHANISMS MUTSMUT.

SAMPL.

KNOWN

DRIVER?

CONNECTED

TO DRIVER?

TP53 2.22E-16 1.19E-13 TP53 CELL CYCLE INHIBITOR 8 6 True True

CDK5RAP1 6.59E-09 1.76E-06 TRANSCRIPTIONAL REGULATION RNA METHYLTHIOTRANSFERASE 2 2

FAT4 4.17E-05 7.43E-03 FOCAL ADHESION & EM CADHERIN 11 6

ADAM8 1.37E-04 1.84E-02 FOCAL ADHESION & EM CELL-CELL & CELL-MATRIX INTERACTIONS 2 2 True

GLB1L2 2.87E-04 3.07E-02 METABOLIC BETA-GALACTOSIDASE ACTIVITY 3 3

CACNA1C 3.82E-04 3.41E-02 CALCIUM VOLTAGE-DEPENDENT CALCIUM CHANNEL 2 2 True

OGG1 5.18E-04 3.96E-02 DNA-REPAIR DNA-REPAIR 2 2 True

HIVEP2 6.53E-04 4.37E-02 TRANSCRIPTIONAL REGULATION TRANSCRIPTION FACTOR. 6 4

RB1 8.09E-04 4.81E-02 RB1 CELL CYCLE INHIBITOR 4 2 True True

CIT 1.10E-03 5.87E-02 FOCAL ADHESION & EM GPCR / RHO-RAC 4 3

CLASP2 1.52E-03 7.40E-02 FOCAL ADHESION & EM STABILIZATION OF MICROTUBULES 4 3

MLL3 3.06E-03 1.02E-01 TRANSCRIPTIONAL REGULATION TRANSCRIPTIONAL COACTIVATION 3 3 True

RPS6KB1 4.58E-03 1.23E-01 PI3K/mTOR p70-S6K-mTOR PATHWAY 2 2

PTPRC 5.39E-03 1.37E-01 N/A TYROSINE PHOSPHATASE 3 2 True

HDAC2 5.98E-03 1.40E-01 TRANSCRIPTIONAL REGULATION TRANSCRIPTIONAL REPRESSION 2 2

RPTOR 6.00E-03 1.40E-01 PI3K/mTOR mTOR REGULATOR 4 4

ROS1 7.49E-03 1.60E-01 RTKs RECEPTOR TYROSINE KINASE 3 3 True

NFATC4 8.79E-03 1.68E-01 CALCIUM GPCR/Ca2+

& cAMP 3 2

MAPK8IP3 1.16E-02 1.77E-01 RAS/MAPK PROTEIN SCAFFOLD 3 3

APC 1.70E-02 2.33E-01 WNT ANTAGONIST OF THE WNT SIGNALING 3 3 True

SMARCA4 2.09E-02 2.61E-01 TRANSCRIPTIONAL REGULATION CHROMATIN REMODELING 2 2 True

CRTC3 2.49E-02 2.89E-01 cAMP (CREB) TRANSCRIPTION COACTIVATOR 2 2 True

González-Vela C*, Curiel-Olmo, S*, et al. JID. 2017.

SIGNIFICANTLY MUTATED MECHANISMS FOUND BY ONCODRIVE.


PATHWAY ID

P_VALUE Q_VALUE NAME/MAIN FUNCTION ASSOCIATED MECHANISMS OTHER

hsa05217 3.67E-07 3.94E-05 BASAL CELL CARCINOMA SHH U.V. EXPOSURE

hsa05220 5.36E-07 3.94E-05 CML BCR-ABL TP53, RB

hsa05210 1.95E-06 9.58E-05 COLORECTAL CANCER RAS, APC (WNT) TP53

hsa00280 2.71E-06 9.96E-05 VALINE ISOLEUCINE DEGRADATION METABOLISM N/A

hsa04270 3.87E-06 1.14E-04 VASCULAR SMOOTH MUSCLE CONTRACTION CALCIUM MYOSIN-ACTIN CONTRACTION

hsa04151 1.40E-05 3.22E-04 PI3K-AKT PI3K/mTOR N/A

hsa05222 1.64E-05 3.22E-04 SMALL CELL LUNG CANCER MYC, TP53 RB1

hsa05223 1.75E-05 3.22E-04 NSCLC RAS, ERBB2 (RTK), TP53 N/A

hsa05219 2.55E-05 4.17E-04 BLADDER FGFR3 (RTK)/RAS MATRIX METALLOPROTEASES

hsa05034 4.45E-05 6.42E-04 ALCOHOLISM/CREB ACTIVATION cAMP/CREB GPCR SIGNALLING

hsa05203 4.80E-05 6.42E-04 VIRAL CANCER VIRAL ONCOPROTEINS MULTIPLE MECHANISMS

hsa05212 9.14E-05 1.06E-03 PANCREATIC HER2 (RTK)/RAS/MAPK TP53

hsa05410 9.37E-05 1.06E-03 HYPERTROPHIC CARIOMYOPATHY CALCIUM BINDING TO ACTOMYOSIN ATP IMBALANCE

hsa04810 1.07E-04 1.13E-03 ACTIN CYTOSKELETON CYTOSKELETAL REMODELING N/A

hsa05161 1.27E-04 1.24E-03 HEPATITIS B VIRAL ONCOPROTEINS MULTIPLE MECHANISMS

hsa05166 1.59E-04 1.46E-03 HTLV-1 INFECTION VIRAL ONCOPROTEINS cAMP/CREB, NFAT, NFKB, SRF

hsa05213 2.03E-04 1.75E-03 ENDOMETRIAL CANCER HER2 (RTK)/RAS/MAPK, B-CAT TP53

hsa05200 2.43E-04 1.98E-03 PATHWAYS IN CANCER MULTIPLE MECHANISMS MULTIPLE MECHANISMS

hsa04512 2.73E-04 2.01E-03 EXTRACELLULAR MATRIX EXTRACELLULAR MATRIX N/A

hsa04722 2.74E-04 2.01E-03 NEUROTROPHIN SIGNALING TRK (RTK) MAPK, PLC (CALCIUM)

hsa04115 3.08E-04 2.16E-03 TP53 TP53 N/A

hsa04110 3.60E-04 2.41E-03 CELL CYCLE TP53, RB1 MULTIPLE MECHANISMS

hsa00565 4.38E-04 2.80E-03 ETHER LIPID METABOLISM METABOLISM N/A

hsa05215 6.63E-04 4.06E-03 PROSTATE MULTIPLE MECHANISMS N/A

hsa00640 7.02E-04 4.13E-03 PROPANOATE METABOLISM METABOLISM N/A

hsa05412 7.56E-04 4.28E-03 ARRHYTHOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY MULTIPLE MECHANISMS WNT, CALCIUM

hsa05168 8.95E-04 4.81E-03 HERPEX SIMPLEX INFECTIONS VIRAL ONCOPROTEINS MULTIPLE MECHANISMS

hsa05016 9.16E-04 4.81E-03 HUNTINGTON´S DISEASE MULTIPLE MECHANISMS N/A

hsa04210 1.09E-03 5.51E-03 APOPTOSIS MULTIPLE MECHANISMS N/A

hsa05031 1.16E-03 5.69E-03 AMPHETAMINE ADDICTION/CREB ACTIVITY cAMP/CREB FOS, FOSB

hsa05214 2.44E-03 1.16E-02 GLIOMA MULTIPLE MECHANISMS TP53, RB

hsa05414 2.56E-03 1.18E-02 DILATED CARDIOMYOPATHY MULTIPLE MECHANISMS cAMP/CREB, CALCIUM

hsa04727 2.77E-03 1.23E-02 GABAERGIC SYNAPSE MULTIPLE MECHANISMS SECONDARY MESSENGERS

hsa04150 3.34E-03 1.45E-02 mTOR SIGNALING mTOR N/A

hsa05162 3.57E-03 1.50E-02 MEASELS VIRAL ONCOPROTEINS JAK/STAT

hsa04360 5.01E-03 1.99E-02 AXON GUIDANCE MULTIPLE MECHANISMS RHO GTPASES (CYTOSKELETON)

hsa04010 5.13E-03 1.99E-02 MAPK SIGNALING MAPK N/A

hsa04910 5.16E-03 1.99E-02 INSULIN SIGNALING INSR (RTK) MULTIPLE MECHANISMS

hsa05216 5.64E-03 2.13E-02 THYROID CANCER RET, TRK (RTKs) RAS, TP53

hsa04724 1.05E-02 3.86E-02 GLUTAMINERGIC SIGNALING MULTIPLE MECHANISMS GPCR SIGNALLING

hsa04310 1.09E-02 3.90E-02 WNT WNT N/A

hsa05202 1.30E-02 4.56E-02 TRANSCRIPTIONAL MISREGULATION IN CANCER MULTIPLE MECHANISMS MULTIPLE MECHANISMS

hsa04930 1.40E-02 4.77E-02 TYPE II DIABETES MELLITUS MULTIPLE MECHANISMS MULTIPLE MECHANISMS

hsa05160 1.54E-02 5.14E-02 HEPATITIS C VIRAL ONCOPROTEINS MULTIPLE MECHANISMS

hsa05218 1.67E-02 5.46E-02 MELANOMA MULTIPLE MECHANISMS U.V. EXPOSURE

hsa04514 1.97E-02 6.30E-02 CELL ADHESION PROTEINS CELL ADHESION MULTIPLE MECHANISMS

hsa04510 2.29E-02 7.18E-02 FOCAL ADHESION MULTIPLE MECHANISMS ACTIN CYTOKELETON

hsa04146 2.94E-02 9.01E-02 PEROXISOME N/A N/A

hsa05014 3.31E-02 9.94E-02 AMYOTROPHIC LATERAL SCLEROSIS (ALS) MULTIPLE MECHANISMS MULTIPLE MECHANISMS

hsa04012 3.54E-02 1.03E-01 ERBB SIGNALING RTKs MULTIPLE MECHANISMS

hsa04530 3.58E-02 1.03E-01 TIGHT JUNCTION MULTIPLE MECHANISMS MULTIPLE MECHANISMS

hsa05010 4.63E-02 1.31E-01 ALZHEIMER DISEASE MULTIPLE MECHANISMS MULTIPLE MECHANISMS

Missense

Nonsense

UTR region

MCPyV

FOCAL ADHESION & EXTRACELLULAR MATRIX

TRANSCRIPTIONAL REGULATION

METABOLISM

CALCIUM

WNT

cAMP/CREB

RAS/MAPK

RTKs

PI3K/mTOR

OTHER

DISTRIBUTION OF MUTATIONS IN SIGNIFICANT GENES AND PATHWAYS Mutational Rate

González-Vela C*, Curiel-Olmo, S*, et al.

JID. 2017.

BIOMARKERS ASSOCIATED TO DEREGULATED MECHANISMS

END-POINT (T.F.) ACTIVATING MECHANISM

C-MYC RTKs, RAS/MAPK, PI3K/mTOR

P-STAT3 JAK/STAT, RTKs

P-CREB cAMP/CREB signaling

LEF1 WNT, MYC

NFAT Calcium signaling

HIGHLY SIGNIFICANT GENES

(PROTEINS) IN OUR ANALYSIS

TP53

RB1

PREVIOUSLY REPORTED

p63

POLYOMAVIRAL INTEGRATION

MCPyV-LT antigen

MCPyV

TP53

RB

POSITIVE NEGATIVE


EXAMPLES OF MCC SAMPLES FROM PATIENTS CHARACTERIZED BY IHC


ASSESSMENT OF DISEASE MECHANISMS IN A LARGER COHORT

Immunohistochemistry: 48 cases 27/48 cases: MCPyV-positive (56 %).

21/48 cases: MCPyV-negative (44 %). CASE MCPyV p63 NFAT-C1 P-CREB P-STAT-3 P53 RB MYC LEF1-L

8 POSITIVE N/D N/D N/D N/D N/D N/D N/D N/D

9 POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

10 POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE NEGATIVE LOSS NEGATIVE NEGATIVE

11 POSITIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

12 POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

14 POSITIVE POSITIVE POSITIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

15 POSITIVE POSITIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE POSITIVE POSITIVE NEGATIVE

16 POSITIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE


18 POSITIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE LOSS NEGATIVE NEGATIVE

19 POSITIVE POSITIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

20 POSITIVE POSITIVE POSITIVE NEGATIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

21 POSITIVE POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE


23 POSITIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

24 POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE




28 POSITIVE N/D NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

29 POSITIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

30 POSITIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

31 POSITIVE POSITIVE POSITIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE

32 POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE POSITIVE

33 POSITIVE POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

34 POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

35 POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

1 NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE

2 NEGATIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE LOSS NEGATIVE POSITIVE

3 NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE

4 NEGATIVE POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE LOSS NEGATIVE NEGATIVE

5 NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE POSITIVE LOSS POSITIVE NEGATIVE

6 NEGATIVE POSITIVE NEGATIVE NEGATIVE POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE

7 NEGATIVE POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE

13 NEGATIVE N/D NEGATIVE N/D N/D N/D N/D N/D N/D

36 NEGATIVE POSITIVE POSITIVE NEGATIVE NEGATIVE POSITIVE LOSS NEGATIVE NEGATIVE

37 NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE LOSS POSITIVE POSITIVE

38 NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE LOSS NEGATIVE NEGATIVE

39 NEGATIVE POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE LOSS NEGATIVE NEGATIVE

40 NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE LOSS NEGATIVE NEGATIVE

41 NEGATIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE

42 NEGATIVE POSITIVE NEGATIVE POSITIVE NEGATIVE NEGATIVE POSITIVE NEGATIVE POSITIVE

43 NEGATIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE POSITIVE LOSS POSITIVE NEGATIVE

44 NEGATIVE NEGATIVE POSITIVE NEGATIVE POSITIVE POSITIVE LOSS NEGATIVE NEGATIVE

45 NEGATIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE NEGATIVE LOSS NEGATIVE NEGATIVE

46 NEGATIVE POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE POSITIVE NEGATIVE

47 NEGATIVE NEGATIVE POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE

48 NEGATIVE POSITIVE POSITIVE POSITIVE POSITIVE NEGATIVE POSITIVE POSITIVE POSITIVE

González-Vela C*, Curiel-Olmo, S*, et al.

JID. 2017.

α

COMMON AND DIVERGENT DISEASE MECHANISMS FOUND IN MCC

RAS

JAK RHO/RAC

mTOR

β γ

β γ

LEF1

4 % 33 %

NFAT

42 % 33 %

P-CREB

35 % 60 %

FOCAL ADHESION & EM GPCR SIGNALING RTK SIGNALING

GNAS

GRM1-6 ERBB4, MET

ADCY

GNAI G-ACTIN

F-ACTIN

ITGB4, FAT4

TP53

37 % 57 %

RB

7 % 52 %

GNAQ

p63

50 % 70 %

CALCIUM cAMP/CREB ACTIN CYTOSKELETON

MALIGNANT MCC TRANSCRIPTION

MAPK

MYC

4 % 45 %

MCPyV + MCPyV -

P-STAT

55 % 15 %

PLCB1

PI3K

FLNC

COL24A1, COL4A4

SHARED


MCC : BIOMARKES AND SURVIVAL-I


ASOCIATION OF BIOMARKERS WITH SURVIVAL OF PATIENTS

P-STAT

0 1000 2000 3000 4000 5000 0

20

40

60

80

100

P-STAT positive

P-STAT negative

Pe

rce

nt

su

rviv

al (%

)

Time (days)

p=0.024

0 1000 2000 3000 4000 5000 0

20

40

60

80

100

P-CREB positive

P-CREB negative

Time (days)

Pe

rce

nt

su

rviv

al (%

)

P-CREB

p=0.011

Hazard Ratios for P-CREB and STAT markers, in relation to mortality.

Multivariate analysis against: sex, age, stage, MCPyV, P-STAT, P-CREB.

a HRc = Crude Hazard Ratio.

b HRa = Hazard Ratio adjusted for P-CREB, P-STAT, MCPyV status, sex, age and stage.

Vital status

Death

(n=15)

Survival

(n=33) HRca (95% CI) HRab (95% CI)

P-CREB

Negative 5 20 1 -- 1 --

Positive 9 12 3.89 1.28 11.87 5.56 1.22 25.33

P-STAT

Negative 7 24 1 -- 1 --

Positive 7 8 3.37 1.1 10.3 1.65 0.22 12.35


LESSONS LEARNED FROM MERKEL CELL CARCINOMA

MCC TUMORS SHOW MULTIPLE GENOMIC SIMILIARITIES TO LUNG CANCER (SCLC, NSCLC) AND CUTANEOUS MELANOMA

DESPITE IMPORTANT GENETIC DIFFERENCES BETWEEN MCPyV+ AND MCPyV- CASES, MCC TUMORS CAN DEVELOP SIMILAR MECHANIMS OF DISEASE. 1) WES ANALYSES HELPED IDENTIFYING IMPORTANT MECHANISMS OF DISEASE. SOME ACTIONABLE? 2) ASSOCIATED BIOMARKES SHOWED POTENTIAL TO BE USED IN PROGNOSYS, AND THERAPY?

• VALIDATE OUR FINDINGS_INDEPENDENT COHORT OF CASES WITH CLINICAL DATA

• EXPLORE THE MECHANISTIC NATURE REGARDING THE SHARED MECHANISMS BETWEEN MCC ETIOLOGIES

• ALSO SPECIFIC MCPyV- MECHANISMS AND BIOMARKERS

• ARE THESE POTENTIAL BIOMARKERS USEFUL TO PREDICT THERAPEUTIC RESPONSES TO IMMUNOTHERAPY

• IMMUNOTHERAPY SHOWS EFFECT IN UP TO 50% OF PATIENTS

• IMMUNOTHERAPY WORKS SIMILARLY IN:

A) MCPyV+ CASES EXPRESSING VIRAL ANTIGENS B) MCPyV- CASES EXPRESSING HIGH NUMBER OF NEOEPITOPES (HIGH M.Is. AND UV SIGNATURES)

ACKNOWLEDGMENTS

IDIVAL

U.A. DE ONCOLOGÍA-HUMV

•Soraya Curiel-Olmo •Nerea Martinez

•Almudena García Castaño

S. ANATOMIA PATOLÓGICA-HUMV

•Ignacio Varela •Antonio Manuel Agraz-Doblas •Helena Pisonero

U. CANTABRIA-IBBTEC BIOBANCO HUMV-IDIVAL

•Laura Cereceda •Santiago Montes •José Revert

•Pablo Isidro-Marron

BIOBANCO-H. CENTRAL DE ASTURIAS

Contact information: Dr. José P. Vaqué: [email protected] Dra. Almudena García Castaño: [email protected] Dra. Carmen González-Vela: [email protected]

S. DERMATOLOGÍA, H12O:

•Pablo Ortiz-Romero •Carmen González-Vela

•Ivo Gut •Martha Gut •Sergi Beltrán •Sophia Derdak

CNAG-CRG S. DERMATOLOGÍA-IVO

•Beatriz LLombart

IARC-WHO

•Linnette Fernandez-Cuesta

UNIVERSITY OF GRAZ

•Lorenzo Cerroni

BIOBANCO IVO

•José A. López Guerrero

ESTADÍSTICA UC

•Miguel Santibáñez

FUNDACIÓN JIMÉNEZ DÍAZ

•Miguel Á. Piris

mailto:[email protected]



ACKNOWLEDGEMENTS

U.A. DE ONCOLOGÍA-HUMV

IDIVAL •Soraya Curiel-Olmo •Nerea Martinez

•Almudena García-Castaño

•Ignacio Varela •Antonio Manuel Agraz

BIOBANCO DE TUMORES SÓLIDOS,

HUMV-IDIVAL

•Laura Cereceda •Santiago Montes •José Revert

Contact information: Dr. José P. Vaqué: [email protected]

SERVICIO DE DERMATOLOGÍA, H12O:

•Pablo Ortiz-Romero

•Miguel Ángel Piris

S. ANATOMIA PATOLÓGICA-HUMV

•Carmen González-Vela

UC-IBBTEC • •Helena Pisonero


DIFFERENTIAL DIAGNOSIS OF MCC

» Small Cell Lung Cancer (SCLC) shares many cellular and tissular characteristics with MCC.

OVERLAPPING: Different neoplasms show similar characteristics in both clinic and morphology.

DIFFERENTIAL DIAGNOSIS

MCC: Cytokeratin 20 (CK20) expression.

However,

- 5 % of MCCs lack CK20 expression.

- Other cancers (i.e. colorectal) express CK20.

Interesting since it is possible that MCC data could be extrapolated to SCLC

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