SlideShare uma empresa Scribd logo
1 de 22
Baixar para ler offline
MULTIPLE MYELOMA: NEW SURFACE ANTIGENS FOR THE
CHARACTERIZATION OF PLASMA CELLS IN THE ERA OF NOVEL AGENTS
Vittorio Emanuele Muccio
Laboratorio di Citofluorimetria Divisione Universitaria Ematologia Prof. M. Boccadoro
Azienda Ospedaliero Universitaria Città della Salute e della Scienza di Torino
Incontri informali di aggiornamento e confronto sulla ricerca di laboratorio
Divisione Universitaria di Ematologia - Torino
Vittorio Emanuele Muccio
Citofluorimetria: come funziona
Vittorio Emanuele Muccio
Citofluorimetria: come funziona
Vittorio Emanuele Muccio
Citofluorimetria: finalità
Caratterizzare
QuantificareIdentificare
Vittorio Emanuele Muccio
Le plasmacellule in citofluorimetria
Marcatori per
identificare le
plasmacellule
Marcatori per
identificare le
plasmacellule
MALIGNE
Vittorio Emanuele Muccio
Marcatori per identificare le plasmacellule
CD38
perché?
CD138
perché?
CD40
Linfociti B e Antigen-Presenting Cells
CD31
Piastrine, monociti, neutrofili e linfociti T
Vittorio Emanuele Muccio
Marcatori utilizzati per identificare le plasmacellule maligne
CD117
CD13
CD14CD15
CD20
CD10
CD27 CD19
CD9
CD11bCD40
CD31
CD41
CD56
CD45
CD28
CD23
CD22
CD33 CD24
CD25
CD37
CD39
CD71
HLA-DR
CD44 CD4
CD8
CD81
CD38
CD200
Vittorio Emanuele Muccio
Marcatori più utilizzati nell’identificazione delle
plasmacellule maligne
Espressione monoclonale delle catene
intracitoplasmatiche kappa o lambda
Linfociti NK
CD56
Cellule mieloidi
CD117
CD33
Linfociti T
CD27
CD28
CD45
Linfociti B/PC
CD27
CD19
CD20
CD81
CD10
Tohami et al. 2007 FASEB J
Paiva et al. 2012 Leukemia
Robillard et al. 1998 Clin Cancer Res.
Guo et al. 2015 Haematology
Shim et al. 2014 Biomed Res Int.
Sahara et al. 2006 Eur J Haematol
Moureau et al. 2004 Haematologica
Pellat-Deceunynck et al. 2004 Blood Cells Mol Dis
Kumar et al. 2005 Leukemia
Guo et al. 2015 Haematologica
Liu et al. 2014 Hematol Oncol
Bataille et al. 2008 Leuk Res
Guo et al 2015 Haematologica
= Espressione ridotta nelle PC di
MM rispetto alle PC sane
= Espressione aumentata nelle PC
di MM rispetto alle PC sane
= Espressione correlata a prognosi
favorevole
= Espressione correlata a prognosi
sfavorevole o ridotta
sopravvivenza
Vittorio Emanuele Muccio
9th International Conference on
Human Leukocyte Differentiation Antigens (HLDA9)
82 Molecole di superficie
5 Linee cellulari di MM20 MM alla diagnosi
Vittorio Emanuele Muccio
Famiglie in cui è possibile raggruppare gli antigeni studiati
SIALOADESINE
SLAM
INTEGRINETNF/TNFR
IRTA
CITOCHINE-R
CHEMOCHINE-R CD28/B7TLR/C-TYPE LEC R
Vittorio Emanuele Muccio
#mAb CD LP1 U266 OPM-2 NCI-H929 KMS-12-BM
29 CD86 1,0 6,3 2,3 13,4 74,1
33 CD83 64,8 1,8 1,0 1,5 43,0
34 CD152 (CTLA-4) 2,5 5,8 27,3 9,6 3,1
36 CD126 30,5 82,7 98,7 91,9 97,1
41 CD130 1,0 32,4 58,4 7,7 22,9
46 CD184 98,4 58,1 45,7 1,0 84,3
55 DR4 1,8 4,9 56,0 2,3 44,1
57 DR5 95,6 1,7 29,1 17,0 63,2
85 GITR 3,3 97,7 17,8 10,3 18,7
86 CD229 (Ly9) 89,6 92,7 99,7 96,1 6,1
87 CD319 (CRACC) 2,2 3,3 99,9 20,7 6,7
88 CD48 14,4 3,5 99,8 86,2 34,4
89 CD84 29,4 1,4 1,5 2,4 1,0
93 NTBA 41,3 98,0 1,0 1,9 1,0
94 HVEM (TR2) 15,2 34,4 10,8 25,7 97,9
235 BAFF-R 1,0 1,5 1,0 2,7 96,1
237 BAFF 5,2 33,5 87,0 88,5 57,9
239 B7-H2 1,7 3,8 2,2 10,5 44,5
242 LAIR1 92,4 1,8 1,0 2,3 1,0
Antigeni positivi in almeno una linea cellulare di MM
Vittorio Emanuele Muccio
# mAb Specificity Conjugated fluorochrome CD Isotype Ab Species % of positive MM
samples
20 FCRL1 PE CD307a IgG1k Mouse 0
21 FCRL2 PE CD307b IgG2Ak Mouse 0
22 FCRL3 PE CD307c IgG2Bk Mouse 0
23 FCRL4 PE CD307d IgG2Ak Mouse 0
28 Siglec-7 PE CD328 IgG1k Mouse 0
29 B7-2 PE CD86 IgG1k Mouse 64*
30 IL-10R PE CD210 IgG2ak Rat 0
31 CCR7 PE CD197 IgG2ak Rat 0
32 Siglec-9 PE CDw329 IgG1k Mouse 0
33 HB15 PE CD83 IgG1k Mouse 0
34 CTLA-4 PE CD152 IgG2ak Mouse 0
35 B7-1 PE CD80 IgG1k Mouse 0
36 IL6-Rα PE CD126 IgG1k Mouse 45
37 PD1 PE CD279 IgG1k Mouse 0
38 B7-DC PE CD273 IgG1k Mouse 0
39 IL-4Rα PE CD124 IgG1k Mouse 0
40 OX2 PE CD200 IgG1k Mouse 70*
41 gp130 PE CD130 IgG1k Mouse 45
42 IL-12R PE CD212 IgG1k Mouse 0
43 Siglec PE CD328 IgG1k Mouse 0
44 CCR2 A647 CD192 IgG2b Mouse 18
45 ICOS PE CD278 IgG1 Mouse 0
46 CXCR4 PE CD184 IgG2ak Mouse 64*
47 BTLA PE CD272 IgG1k Mouse 64*
48 CCR6 PE CD196 IgG1k Mouse 18
49 TACI PE CD267 IgG2ak Rat 0
50 CXCR5 A647 CD185 IgG2bk Rat 45
51 Integrin beta 7 chain PE NONE IgG2ak Rat 0
52 CCR1 A647 CD191 IgG2bk Mouse 27
53 Integrin beta 5 PE NONE IgG1 k Mouse 0
54 B7-H4 PE NONE IgG1 k Mouse 0
55 DR4 PE CD271 IgG1 k Mouse 0
56 CMKLR1 PE NONE IgG2a k Rat 0
57 DR5 PE CD262 IgG1 k Mouse 18
74 Integrin beta 6 PE NONE IgG2b Mouse 0
75 Dectin-1/CLEC7A PE NONE IgG2b Mouse 0
76 TREM-1 PE NONE IgG1 Mouse 10
77 Siglec-5/Siglec-14 APC CD170 IgG1 Mouse 0
78 AMICA PE NONE IgG2a Mouse 0
79 BLT1/LTB4R1 PE NONE IgG1 Mouse 10
80 Siglec-9 APC CD329 IgG2a Mouse 0
81 IL-23-R PE NONE IgG2b Mouse 9
82 Integrin alfaVbeta5 PE NONE IgG1 Mouse 0
83 CRTAM PE CD355 IgG2b Mouse 0
84 DCIR/CLEC4A PE NONE IgG1 Mouse 0
85 GITR PE NONE IgG1k Mouse 0
86 Ly9 PE CD229 IgG1k Mouse 100*
87 CRACC PE CD319 IgG2b k Mouse 100*
88 BLAST-1 PE CD48 IgG1k Mouse 100*
89 SLAMF5 PE CD84 IgG2a k Mouse 17
90 Toll-like Receptor 3 PE CD283 IgG2a k Mouse 0
91 DcR3 PE NONE IgG1k Mouse 9
92 DR3 (TRAMP) PE NONE IgG1k Mouse 0
93 NTBA PE NONE IgG1k Mouse 100*
94 HVEM PE CD270 IgG1k Mouse 45
95 TSLPR PE NONE IgG1k Mouse 0
96 TWEAK PE CD255 IgG3 k Mouse 0
97 TCL1 PE NONE IgG2b k Mouse 0
98 Galectin-3 (Mac-2) PE NONE IgG1k Mouse 0
99 GITR-L PE NONE IgG1k Mouse 0
100 Lymphotoxin beta receptor PE NONE IgG2b k Mouse 0
101 TREM-1 PE NONE IgG1k Mouse 0
106 SLAM PE CD150 IgG1k Mouse 67*
109 S1PR1 PE CD363 IgG2B Mouse 0
234 IL-15Ralfa PE NONE IgG2b k Mouse 0
235 BAFF-R PE CD268 IgG1 k Mouse 20
236 LIGHT PE CD258 IgG2b k Mouse 20
237 BAFF PE CD257 IgG1 k Mouse 40
238 CD274 PE CD274 IgG2b k Mouse 45
239 B7-H2 PE CD275 IgG2b k Mouse 20
240 CD267 PE CD267 IgG2a k Rat 20
241 NKG2D PE CD314 IgG1 Mouse 0
242 LAIR1 PE CD305 IgG2b Mouse 0
243 DEP-1 PE CD148 IgG1 Mouse 20
244 Syndecan-2 PE NONE IgG2b Rat 20
245 CXCR7/RDC-1 PE NONE IgG2a Mouse 0
246 IL21R PE NONE IgG1 Mouse 0
247 Toll-like Receptor 9 PE CD289 IgG2a k Rat 0
249 TACI PE CD267 IgG2a Mouse 40
250 ABCG2 PE CDw338 IgG2b k Mouse 0
251 BR3 PE CD268 IgG2a k Mouse 0
252 BLyS PE CD257 IgG1 k Mouse 0
Nella colonna di
destra è riportata la
percentuale di
pazienti alla diagnosi
di MM positivi per
quel determinato
antigene. Solo gli
antigeni espressi in
>50% dei pazienti
sono stati selezionati
per la fase successiva
dello studio.
#
mAb
Specificity Conjugated
fluorochrome
CD Isotype Ab Species % of positive
MM samples
29 B7-2 PE CD86 IgG1k Mouse 64*
40 OX2 PE CD200 IgG1k Mouse 70*
46 CXCR4 PE CD184 IgG2ak Mouse 64*
47 BTLA PE CD272 IgG1k Mouse 64*
86 Ly9 PE CD229 IgG1k Mouse 100*
87 CRACC PE CD319 IgG2b k Mouse 100*
88 BLAST-1 PE CD48 IgG1k Mouse 100*
93 NTBA PE NONE IgG1k Mouse 100*
106 SLAM PE CD150 IgG1k Mouse 67*
Anticorpi testati
Vittorio Emanuele Muccio
Seconda fase dello studio
24 nuove diagnosi MM 8 recidive di MM 6 PCL
13 soggetti sani
CD86 CD200 CD272 CD184
CD229 CD319 CD352 CD150
CD48
Vittorio Emanuele Muccio
Percentuale di PC positive
0
20
40
60
80
100
120
CD150 CD229 NTBA CD319 CD48 CD272 CD184 CD28 CD200
Percentage of positive PCs
pc poli mm dia
mm rec pcl
*
*
*
*
°
°
Vittorio Emanuele Muccio
Percentuale di PC positive
%PC
Healthy MM diagnosis MM relapse PCL Kruskal-Wallis
(Post test
p-value)
Median
(range)
Median
(range)
Median
(range)
Median
(range)
CD150 84.2
(48 - 98.7)
57.05
(3.3 - 100)
15
(6.2 - 99.4)
86.3
(1.8 - 99.8)
0.231
(ns)
CD319 99.3
(95.7 - 100)
96.1
(51.5 - 100)
96.4
(54 - 100)
82.65
(51.9 - 99.5)
0.044
(ns)
CD229 94
(79 - 99.7)
94.55
(36 - 100)
96.15
(77.7 - 100)
99.1
(44 - 99.7)
0.926
(ns)
CD352 99.3*
(96.2 - 100)
83.2*
(5.6 - 100)
95.45
(9.9 - 100)
78.2
(17.5 - 99.6)
0.027
(*0.033)
CD48 95.3
(39.6 - 100)
99.45
(82.2 - 100)
92.8
(2.3 - 99.9)
98.6
(3.5 - 100)
0.087
(ns)
CD86 62.6
(20 - 98.6)
48.8
(3.1 - 100)
72.2
(9.3 - 95.3)
81.6
(10 - 96.8)
0.581
(ns)
CD272 85
(46 - 99.6)
91.75
(3.3 - 100)
77.7
(4 - 100)
99.4
(18 - 100)
0.396
(ns)
CD200 15*
(4.8 - 66.9)
65.2*°
(2 - 99.7)
8.15°
(1.3 - 91)
34
(1.4 - 97.5)
0.001
(*0.003)
(°0.024)
CD184 54.4
(13.7 - 94.7)
47.4
(2 - 100)
14.65
(1.3 - 83)
19.2
(2.4 - 90.8)
0.129
(ns)
Vittorio Emanuele Muccio
Mean fluorescence Intensity delle PC positive
0
2000
4000
6000
8000
10000
12000
CD150 CD229 CD352 CD319 CD48 CD272 CD184 CD86 CD200
MFI of positive PCs
MM Diangosis
MM Relapse
PCL
Healthy
*
*
*
*
^
^
^
^
*
*
+
+
Vittorio Emanuele Muccio
Mean fluorescence Intensity delle PC positive
MFI
Healthy MM diagnosis MM relapse PCL Kruskal-Wallis
(Post test
p-value)
Median
(range)
Median
(range)
Median
(range)
Median I
(range)
CD150 2851*
(982 - 4711)
899*
(0 - 7352)
467
(56 - 4866)
1237.5
(106-3419)
0.008
(*0.012)
CD319 4433*^
(1890 - 9055)
1742.5*
(363 - 4093)
1199.5
(179 - 5024)
859^
(674 - 1461)
< 0.001
(*< 0.001)
(^0.004)
CD229 4369^
(1905- 6532)
2923.5
(625 - 8774)
3189
(663 - 9494)
2033.5^
(518 - 3359)
0.051
(^0.045)
CD352 7819*+
(1607- 11560)
2237*
(108 - 11909)
2191.5+
(388 - 6734)
1636.5
(148 - 3124)
< 0.001
(*< 0.001)
(+
0.008)
CD48 11300
(2344 - 25808)
10526.5
(2133-40378)
5978.5
(59 - 48388)
8196
(257 - 18189)
0.370
(ns)
CD86 1543
(527 - 5422)
717.5
(60 - 6633)
1492.5
(526 - 2387)
858
(150 - 1743)
0.262
(ns)
CD272 6150
(917 - 10705)
5745.5
(0 - 28420)
2909.5
(47 - 16996)
5107
(861 - 8844)
0.606
(ns)
CD200 356
(38 - 4498)
1036.5
(0 - 5099)
251
(12.1 - 2322)
273.5
(112-1027)
0.013
(ns)
CD184 1200
(213 - 5922)
1617.5
(0 - 9005)
323.5
(0 - 3237)
241
(90 - 4956)
0.223
(ns)
Vittorio Emanuele Muccio
0
20
40
60
80
100
CD150 CD229 CD352 CD319 CD48 CD272 CD184 CD86 CD200
Positive samples %
MM diagnosis
MM relapse
PCL
Healthy
+
+
*
* *
*
*
*
°
°
Percentuali di pazienti positivi
Pazienti positivi: pazienti in cui più
del 20% delle PC esprime un
determinato antigene.
Vittorio Emanuele Muccio
Conclusioni
CD150, CD86 e CD200
possono aiutare a differenziare PC sane da PC tumorali
Utili nella caratterizzazione delle PC nello studio della
MRD dopo terapia con Lorvotuzumab (anti-CD56) o
Dacetuzumab e Lucatumumab (anti-CD40)Vittorio Emanuele Muccio
Conclusioni
CD272, CD319, CD229 e CD48
sono espressi ad alta intensità dalle PC
Bersagli
terapeutici?
Vittorio Emanuele Muccio
Conclusioni
Utili nella caratterizzazione
delle PC nello studio della
MRD dopo terapia con
BT062 (anti-CD138) o
Daratumumab (anti-CD38)
Vittorio Emanuele Muccio
Grazie per l’attenzione
Vittorio Emanuele Muccio

Mais conteúdo relacionado

Último

Oman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptx
Oman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptxOman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptx
Oman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptxraffaeleoman
 
Iuzzolino Nuria-lavoro scienzeeeeee.pptx
Iuzzolino Nuria-lavoro scienzeeeeee.pptxIuzzolino Nuria-lavoro scienzeeeeee.pptx
Iuzzolino Nuria-lavoro scienzeeeeee.pptxnuriaiuzzolino1
 
Imodelli_atomici_stefano_afferrante.pptx
Imodelli_atomici_stefano_afferrante.pptxImodelli_atomici_stefano_afferrante.pptx
Imodelli_atomici_stefano_afferrante.pptxlorenzodemidio01
 
I Modelli Atmoci_FilippoLuciani bohr.pptx
I Modelli Atmoci_FilippoLuciani bohr.pptxI Modelli Atmoci_FilippoLuciani bohr.pptx
I Modelli Atmoci_FilippoLuciani bohr.pptxfilippoluciani9
 
relazione laboratorio_Stefano Afferrante.docx
relazione laboratorio_Stefano Afferrante.docxrelazione laboratorio_Stefano Afferrante.docx
relazione laboratorio_Stefano Afferrante.docxlorenzodemidio01
 
ModelliAtomici.pptx studente liceo scientifico
ModelliAtomici.pptx studente liceo scientificoModelliAtomici.pptx studente liceo scientifico
ModelliAtomici.pptx studente liceo scientificoyanmeng831
 
I Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptx
I Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptxI Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptx
I Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptxtecongo2007
 
matematicaesempio--power point provaaaaa
matematicaesempio--power point provaaaaamatematicaesempio--power point provaaaaa
matematicaesempio--power point provaaaaanuriaiuzzolino1
 
CamploneAlessandro_ArcheoBatteri (1).pptx
CamploneAlessandro_ArcheoBatteri (1).pptxCamploneAlessandro_ArcheoBatteri (1).pptx
CamploneAlessandro_ArcheoBatteri (1).pptxcamplonealex26
 

Último (9)

Oman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptx
Oman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptxOman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptx
Oman_Raffaele_Progetto_scienze_Eubatteri - Copia (1).pptx
 
Iuzzolino Nuria-lavoro scienzeeeeee.pptx
Iuzzolino Nuria-lavoro scienzeeeeee.pptxIuzzolino Nuria-lavoro scienzeeeeee.pptx
Iuzzolino Nuria-lavoro scienzeeeeee.pptx
 
Imodelli_atomici_stefano_afferrante.pptx
Imodelli_atomici_stefano_afferrante.pptxImodelli_atomici_stefano_afferrante.pptx
Imodelli_atomici_stefano_afferrante.pptx
 
I Modelli Atmoci_FilippoLuciani bohr.pptx
I Modelli Atmoci_FilippoLuciani bohr.pptxI Modelli Atmoci_FilippoLuciani bohr.pptx
I Modelli Atmoci_FilippoLuciani bohr.pptx
 
relazione laboratorio_Stefano Afferrante.docx
relazione laboratorio_Stefano Afferrante.docxrelazione laboratorio_Stefano Afferrante.docx
relazione laboratorio_Stefano Afferrante.docx
 
ModelliAtomici.pptx studente liceo scientifico
ModelliAtomici.pptx studente liceo scientificoModelliAtomici.pptx studente liceo scientifico
ModelliAtomici.pptx studente liceo scientifico
 
I Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptx
I Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptxI Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptx
I Modelli Atomici: Bhor, Rutherford, Dalton, Thomson.pptx
 
matematicaesempio--power point provaaaaa
matematicaesempio--power point provaaaaamatematicaesempio--power point provaaaaa
matematicaesempio--power point provaaaaa
 
CamploneAlessandro_ArcheoBatteri (1).pptx
CamploneAlessandro_ArcheoBatteri (1).pptxCamploneAlessandro_ArcheoBatteri (1).pptx
CamploneAlessandro_ArcheoBatteri (1).pptx
 

Destaque

AI Trends in Creative Operations 2024 by Artwork Flow.pdf
AI Trends in Creative Operations 2024 by Artwork Flow.pdfAI Trends in Creative Operations 2024 by Artwork Flow.pdf
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
 
PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
 
Content Methodology: A Best Practices Report (Webinar)
Content Methodology: A Best Practices Report (Webinar)Content Methodology: A Best Practices Report (Webinar)
Content Methodology: A Best Practices Report (Webinar)contently
 
How to Prepare For a Successful Job Search for 2024
How to Prepare For a Successful Job Search for 2024How to Prepare For a Successful Job Search for 2024
How to Prepare For a Successful Job Search for 2024Albert Qian
 
Social Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie InsightsSocial Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie InsightsKurio // The Social Media Age(ncy)
 
Trends In Paid Search: Navigating The Digital Landscape In 2024
Trends In Paid Search: Navigating The Digital Landscape In 2024Trends In Paid Search: Navigating The Digital Landscape In 2024
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
 
5 Public speaking tips from TED - Visualized summary
5 Public speaking tips from TED - Visualized summary5 Public speaking tips from TED - Visualized summary
5 Public speaking tips from TED - Visualized summarySpeakerHub
 
ChatGPT and the Future of Work - Clark Boyd
ChatGPT and the Future of Work - Clark Boyd ChatGPT and the Future of Work - Clark Boyd
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
 
Getting into the tech field. what next
Getting into the tech field. what next Getting into the tech field. what next
Getting into the tech field. what next Tessa Mero
 
Google's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search IntentGoogle's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search IntentLily Ray
 
Time Management & Productivity - Best Practices
Time Management & Productivity -  Best PracticesTime Management & Productivity -  Best Practices
Time Management & Productivity - Best PracticesVit Horky
 
The six step guide to practical project management
The six step guide to practical project managementThe six step guide to practical project management
The six step guide to practical project managementMindGenius
 
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...RachelPearson36
 
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Applitools
 
12 Ways to Increase Your Influence at Work
12 Ways to Increase Your Influence at Work12 Ways to Increase Your Influence at Work
12 Ways to Increase Your Influence at WorkGetSmarter
 

Destaque (20)

AI Trends in Creative Operations 2024 by Artwork Flow.pdf
AI Trends in Creative Operations 2024 by Artwork Flow.pdfAI Trends in Creative Operations 2024 by Artwork Flow.pdf
AI Trends in Creative Operations 2024 by Artwork Flow.pdf
 
Skeleton Culture Code
Skeleton Culture CodeSkeleton Culture Code
Skeleton Culture Code
 
PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024PEPSICO Presentation to CAGNY Conference Feb 2024
PEPSICO Presentation to CAGNY Conference Feb 2024
 
Content Methodology: A Best Practices Report (Webinar)
Content Methodology: A Best Practices Report (Webinar)Content Methodology: A Best Practices Report (Webinar)
Content Methodology: A Best Practices Report (Webinar)
 
How to Prepare For a Successful Job Search for 2024
How to Prepare For a Successful Job Search for 2024How to Prepare For a Successful Job Search for 2024
How to Prepare For a Successful Job Search for 2024
 
Social Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie InsightsSocial Media Marketing Trends 2024 // The Global Indie Insights
Social Media Marketing Trends 2024 // The Global Indie Insights
 
Trends In Paid Search: Navigating The Digital Landscape In 2024
Trends In Paid Search: Navigating The Digital Landscape In 2024Trends In Paid Search: Navigating The Digital Landscape In 2024
Trends In Paid Search: Navigating The Digital Landscape In 2024
 
5 Public speaking tips from TED - Visualized summary
5 Public speaking tips from TED - Visualized summary5 Public speaking tips from TED - Visualized summary
5 Public speaking tips from TED - Visualized summary
 
ChatGPT and the Future of Work - Clark Boyd
ChatGPT and the Future of Work - Clark Boyd ChatGPT and the Future of Work - Clark Boyd
ChatGPT and the Future of Work - Clark Boyd
 
Getting into the tech field. what next
Getting into the tech field. what next Getting into the tech field. what next
Getting into the tech field. what next
 
Google's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search IntentGoogle's Just Not That Into You: Understanding Core Updates & Search Intent
Google's Just Not That Into You: Understanding Core Updates & Search Intent
 
How to have difficult conversations
How to have difficult conversations How to have difficult conversations
How to have difficult conversations
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
Time Management & Productivity - Best Practices
Time Management & Productivity -  Best PracticesTime Management & Productivity -  Best Practices
Time Management & Productivity - Best Practices
 
The six step guide to practical project management
The six step guide to practical project managementThe six step guide to practical project management
The six step guide to practical project management
 
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
 
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...
 
12 Ways to Increase Your Influence at Work
12 Ways to Increase Your Influence at Work12 Ways to Increase Your Influence at Work
12 Ways to Increase Your Influence at Work
 
ChatGPT webinar slides
ChatGPT webinar slidesChatGPT webinar slides
ChatGPT webinar slides
 
More than Just Lines on a Map: Best Practices for U.S Bike Routes
More than Just Lines on a Map: Best Practices for U.S Bike RoutesMore than Just Lines on a Map: Best Practices for U.S Bike Routes
More than Just Lines on a Map: Best Practices for U.S Bike Routes
 

Ematolab 2015

  • 1. MULTIPLE MYELOMA: NEW SURFACE ANTIGENS FOR THE CHARACTERIZATION OF PLASMA CELLS IN THE ERA OF NOVEL AGENTS Vittorio Emanuele Muccio Laboratorio di Citofluorimetria Divisione Universitaria Ematologia Prof. M. Boccadoro Azienda Ospedaliero Universitaria Città della Salute e della Scienza di Torino Incontri informali di aggiornamento e confronto sulla ricerca di laboratorio Divisione Universitaria di Ematologia - Torino Vittorio Emanuele Muccio
  • 5. Le plasmacellule in citofluorimetria Marcatori per identificare le plasmacellule Marcatori per identificare le plasmacellule MALIGNE Vittorio Emanuele Muccio
  • 6. Marcatori per identificare le plasmacellule CD38 perché? CD138 perché? CD40 Linfociti B e Antigen-Presenting Cells CD31 Piastrine, monociti, neutrofili e linfociti T Vittorio Emanuele Muccio
  • 7. Marcatori utilizzati per identificare le plasmacellule maligne CD117 CD13 CD14CD15 CD20 CD10 CD27 CD19 CD9 CD11bCD40 CD31 CD41 CD56 CD45 CD28 CD23 CD22 CD33 CD24 CD25 CD37 CD39 CD71 HLA-DR CD44 CD4 CD8 CD81 CD38 CD200 Vittorio Emanuele Muccio
  • 8. Marcatori più utilizzati nell’identificazione delle plasmacellule maligne Espressione monoclonale delle catene intracitoplasmatiche kappa o lambda Linfociti NK CD56 Cellule mieloidi CD117 CD33 Linfociti T CD27 CD28 CD45 Linfociti B/PC CD27 CD19 CD20 CD81 CD10 Tohami et al. 2007 FASEB J Paiva et al. 2012 Leukemia Robillard et al. 1998 Clin Cancer Res. Guo et al. 2015 Haematology Shim et al. 2014 Biomed Res Int. Sahara et al. 2006 Eur J Haematol Moureau et al. 2004 Haematologica Pellat-Deceunynck et al. 2004 Blood Cells Mol Dis Kumar et al. 2005 Leukemia Guo et al. 2015 Haematologica Liu et al. 2014 Hematol Oncol Bataille et al. 2008 Leuk Res Guo et al 2015 Haematologica = Espressione ridotta nelle PC di MM rispetto alle PC sane = Espressione aumentata nelle PC di MM rispetto alle PC sane = Espressione correlata a prognosi favorevole = Espressione correlata a prognosi sfavorevole o ridotta sopravvivenza Vittorio Emanuele Muccio
  • 9. 9th International Conference on Human Leukocyte Differentiation Antigens (HLDA9) 82 Molecole di superficie 5 Linee cellulari di MM20 MM alla diagnosi Vittorio Emanuele Muccio
  • 10. Famiglie in cui è possibile raggruppare gli antigeni studiati SIALOADESINE SLAM INTEGRINETNF/TNFR IRTA CITOCHINE-R CHEMOCHINE-R CD28/B7TLR/C-TYPE LEC R Vittorio Emanuele Muccio
  • 11. #mAb CD LP1 U266 OPM-2 NCI-H929 KMS-12-BM 29 CD86 1,0 6,3 2,3 13,4 74,1 33 CD83 64,8 1,8 1,0 1,5 43,0 34 CD152 (CTLA-4) 2,5 5,8 27,3 9,6 3,1 36 CD126 30,5 82,7 98,7 91,9 97,1 41 CD130 1,0 32,4 58,4 7,7 22,9 46 CD184 98,4 58,1 45,7 1,0 84,3 55 DR4 1,8 4,9 56,0 2,3 44,1 57 DR5 95,6 1,7 29,1 17,0 63,2 85 GITR 3,3 97,7 17,8 10,3 18,7 86 CD229 (Ly9) 89,6 92,7 99,7 96,1 6,1 87 CD319 (CRACC) 2,2 3,3 99,9 20,7 6,7 88 CD48 14,4 3,5 99,8 86,2 34,4 89 CD84 29,4 1,4 1,5 2,4 1,0 93 NTBA 41,3 98,0 1,0 1,9 1,0 94 HVEM (TR2) 15,2 34,4 10,8 25,7 97,9 235 BAFF-R 1,0 1,5 1,0 2,7 96,1 237 BAFF 5,2 33,5 87,0 88,5 57,9 239 B7-H2 1,7 3,8 2,2 10,5 44,5 242 LAIR1 92,4 1,8 1,0 2,3 1,0 Antigeni positivi in almeno una linea cellulare di MM Vittorio Emanuele Muccio
  • 12. # mAb Specificity Conjugated fluorochrome CD Isotype Ab Species % of positive MM samples 20 FCRL1 PE CD307a IgG1k Mouse 0 21 FCRL2 PE CD307b IgG2Ak Mouse 0 22 FCRL3 PE CD307c IgG2Bk Mouse 0 23 FCRL4 PE CD307d IgG2Ak Mouse 0 28 Siglec-7 PE CD328 IgG1k Mouse 0 29 B7-2 PE CD86 IgG1k Mouse 64* 30 IL-10R PE CD210 IgG2ak Rat 0 31 CCR7 PE CD197 IgG2ak Rat 0 32 Siglec-9 PE CDw329 IgG1k Mouse 0 33 HB15 PE CD83 IgG1k Mouse 0 34 CTLA-4 PE CD152 IgG2ak Mouse 0 35 B7-1 PE CD80 IgG1k Mouse 0 36 IL6-Rα PE CD126 IgG1k Mouse 45 37 PD1 PE CD279 IgG1k Mouse 0 38 B7-DC PE CD273 IgG1k Mouse 0 39 IL-4Rα PE CD124 IgG1k Mouse 0 40 OX2 PE CD200 IgG1k Mouse 70* 41 gp130 PE CD130 IgG1k Mouse 45 42 IL-12R PE CD212 IgG1k Mouse 0 43 Siglec PE CD328 IgG1k Mouse 0 44 CCR2 A647 CD192 IgG2b Mouse 18 45 ICOS PE CD278 IgG1 Mouse 0 46 CXCR4 PE CD184 IgG2ak Mouse 64* 47 BTLA PE CD272 IgG1k Mouse 64* 48 CCR6 PE CD196 IgG1k Mouse 18 49 TACI PE CD267 IgG2ak Rat 0 50 CXCR5 A647 CD185 IgG2bk Rat 45 51 Integrin beta 7 chain PE NONE IgG2ak Rat 0 52 CCR1 A647 CD191 IgG2bk Mouse 27 53 Integrin beta 5 PE NONE IgG1 k Mouse 0 54 B7-H4 PE NONE IgG1 k Mouse 0 55 DR4 PE CD271 IgG1 k Mouse 0 56 CMKLR1 PE NONE IgG2a k Rat 0 57 DR5 PE CD262 IgG1 k Mouse 18 74 Integrin beta 6 PE NONE IgG2b Mouse 0 75 Dectin-1/CLEC7A PE NONE IgG2b Mouse 0 76 TREM-1 PE NONE IgG1 Mouse 10 77 Siglec-5/Siglec-14 APC CD170 IgG1 Mouse 0 78 AMICA PE NONE IgG2a Mouse 0 79 BLT1/LTB4R1 PE NONE IgG1 Mouse 10 80 Siglec-9 APC CD329 IgG2a Mouse 0 81 IL-23-R PE NONE IgG2b Mouse 9 82 Integrin alfaVbeta5 PE NONE IgG1 Mouse 0 83 CRTAM PE CD355 IgG2b Mouse 0 84 DCIR/CLEC4A PE NONE IgG1 Mouse 0 85 GITR PE NONE IgG1k Mouse 0 86 Ly9 PE CD229 IgG1k Mouse 100* 87 CRACC PE CD319 IgG2b k Mouse 100* 88 BLAST-1 PE CD48 IgG1k Mouse 100* 89 SLAMF5 PE CD84 IgG2a k Mouse 17 90 Toll-like Receptor 3 PE CD283 IgG2a k Mouse 0 91 DcR3 PE NONE IgG1k Mouse 9 92 DR3 (TRAMP) PE NONE IgG1k Mouse 0 93 NTBA PE NONE IgG1k Mouse 100* 94 HVEM PE CD270 IgG1k Mouse 45 95 TSLPR PE NONE IgG1k Mouse 0 96 TWEAK PE CD255 IgG3 k Mouse 0 97 TCL1 PE NONE IgG2b k Mouse 0 98 Galectin-3 (Mac-2) PE NONE IgG1k Mouse 0 99 GITR-L PE NONE IgG1k Mouse 0 100 Lymphotoxin beta receptor PE NONE IgG2b k Mouse 0 101 TREM-1 PE NONE IgG1k Mouse 0 106 SLAM PE CD150 IgG1k Mouse 67* 109 S1PR1 PE CD363 IgG2B Mouse 0 234 IL-15Ralfa PE NONE IgG2b k Mouse 0 235 BAFF-R PE CD268 IgG1 k Mouse 20 236 LIGHT PE CD258 IgG2b k Mouse 20 237 BAFF PE CD257 IgG1 k Mouse 40 238 CD274 PE CD274 IgG2b k Mouse 45 239 B7-H2 PE CD275 IgG2b k Mouse 20 240 CD267 PE CD267 IgG2a k Rat 20 241 NKG2D PE CD314 IgG1 Mouse 0 242 LAIR1 PE CD305 IgG2b Mouse 0 243 DEP-1 PE CD148 IgG1 Mouse 20 244 Syndecan-2 PE NONE IgG2b Rat 20 245 CXCR7/RDC-1 PE NONE IgG2a Mouse 0 246 IL21R PE NONE IgG1 Mouse 0 247 Toll-like Receptor 9 PE CD289 IgG2a k Rat 0 249 TACI PE CD267 IgG2a Mouse 40 250 ABCG2 PE CDw338 IgG2b k Mouse 0 251 BR3 PE CD268 IgG2a k Mouse 0 252 BLyS PE CD257 IgG1 k Mouse 0 Nella colonna di destra è riportata la percentuale di pazienti alla diagnosi di MM positivi per quel determinato antigene. Solo gli antigeni espressi in >50% dei pazienti sono stati selezionati per la fase successiva dello studio. # mAb Specificity Conjugated fluorochrome CD Isotype Ab Species % of positive MM samples 29 B7-2 PE CD86 IgG1k Mouse 64* 40 OX2 PE CD200 IgG1k Mouse 70* 46 CXCR4 PE CD184 IgG2ak Mouse 64* 47 BTLA PE CD272 IgG1k Mouse 64* 86 Ly9 PE CD229 IgG1k Mouse 100* 87 CRACC PE CD319 IgG2b k Mouse 100* 88 BLAST-1 PE CD48 IgG1k Mouse 100* 93 NTBA PE NONE IgG1k Mouse 100* 106 SLAM PE CD150 IgG1k Mouse 67* Anticorpi testati Vittorio Emanuele Muccio
  • 13. Seconda fase dello studio 24 nuove diagnosi MM 8 recidive di MM 6 PCL 13 soggetti sani CD86 CD200 CD272 CD184 CD229 CD319 CD352 CD150 CD48 Vittorio Emanuele Muccio
  • 14. Percentuale di PC positive 0 20 40 60 80 100 120 CD150 CD229 NTBA CD319 CD48 CD272 CD184 CD28 CD200 Percentage of positive PCs pc poli mm dia mm rec pcl * * * * ° ° Vittorio Emanuele Muccio
  • 15. Percentuale di PC positive %PC Healthy MM diagnosis MM relapse PCL Kruskal-Wallis (Post test p-value) Median (range) Median (range) Median (range) Median (range) CD150 84.2 (48 - 98.7) 57.05 (3.3 - 100) 15 (6.2 - 99.4) 86.3 (1.8 - 99.8) 0.231 (ns) CD319 99.3 (95.7 - 100) 96.1 (51.5 - 100) 96.4 (54 - 100) 82.65 (51.9 - 99.5) 0.044 (ns) CD229 94 (79 - 99.7) 94.55 (36 - 100) 96.15 (77.7 - 100) 99.1 (44 - 99.7) 0.926 (ns) CD352 99.3* (96.2 - 100) 83.2* (5.6 - 100) 95.45 (9.9 - 100) 78.2 (17.5 - 99.6) 0.027 (*0.033) CD48 95.3 (39.6 - 100) 99.45 (82.2 - 100) 92.8 (2.3 - 99.9) 98.6 (3.5 - 100) 0.087 (ns) CD86 62.6 (20 - 98.6) 48.8 (3.1 - 100) 72.2 (9.3 - 95.3) 81.6 (10 - 96.8) 0.581 (ns) CD272 85 (46 - 99.6) 91.75 (3.3 - 100) 77.7 (4 - 100) 99.4 (18 - 100) 0.396 (ns) CD200 15* (4.8 - 66.9) 65.2*° (2 - 99.7) 8.15° (1.3 - 91) 34 (1.4 - 97.5) 0.001 (*0.003) (°0.024) CD184 54.4 (13.7 - 94.7) 47.4 (2 - 100) 14.65 (1.3 - 83) 19.2 (2.4 - 90.8) 0.129 (ns) Vittorio Emanuele Muccio
  • 16. Mean fluorescence Intensity delle PC positive 0 2000 4000 6000 8000 10000 12000 CD150 CD229 CD352 CD319 CD48 CD272 CD184 CD86 CD200 MFI of positive PCs MM Diangosis MM Relapse PCL Healthy * * * * ^ ^ ^ ^ * * + + Vittorio Emanuele Muccio
  • 17. Mean fluorescence Intensity delle PC positive MFI Healthy MM diagnosis MM relapse PCL Kruskal-Wallis (Post test p-value) Median (range) Median (range) Median (range) Median I (range) CD150 2851* (982 - 4711) 899* (0 - 7352) 467 (56 - 4866) 1237.5 (106-3419) 0.008 (*0.012) CD319 4433*^ (1890 - 9055) 1742.5* (363 - 4093) 1199.5 (179 - 5024) 859^ (674 - 1461) < 0.001 (*< 0.001) (^0.004) CD229 4369^ (1905- 6532) 2923.5 (625 - 8774) 3189 (663 - 9494) 2033.5^ (518 - 3359) 0.051 (^0.045) CD352 7819*+ (1607- 11560) 2237* (108 - 11909) 2191.5+ (388 - 6734) 1636.5 (148 - 3124) < 0.001 (*< 0.001) (+ 0.008) CD48 11300 (2344 - 25808) 10526.5 (2133-40378) 5978.5 (59 - 48388) 8196 (257 - 18189) 0.370 (ns) CD86 1543 (527 - 5422) 717.5 (60 - 6633) 1492.5 (526 - 2387) 858 (150 - 1743) 0.262 (ns) CD272 6150 (917 - 10705) 5745.5 (0 - 28420) 2909.5 (47 - 16996) 5107 (861 - 8844) 0.606 (ns) CD200 356 (38 - 4498) 1036.5 (0 - 5099) 251 (12.1 - 2322) 273.5 (112-1027) 0.013 (ns) CD184 1200 (213 - 5922) 1617.5 (0 - 9005) 323.5 (0 - 3237) 241 (90 - 4956) 0.223 (ns) Vittorio Emanuele Muccio
  • 18. 0 20 40 60 80 100 CD150 CD229 CD352 CD319 CD48 CD272 CD184 CD86 CD200 Positive samples % MM diagnosis MM relapse PCL Healthy + + * * * * * * ° ° Percentuali di pazienti positivi Pazienti positivi: pazienti in cui più del 20% delle PC esprime un determinato antigene. Vittorio Emanuele Muccio
  • 19. Conclusioni CD150, CD86 e CD200 possono aiutare a differenziare PC sane da PC tumorali Utili nella caratterizzazione delle PC nello studio della MRD dopo terapia con Lorvotuzumab (anti-CD56) o Dacetuzumab e Lucatumumab (anti-CD40)Vittorio Emanuele Muccio
  • 20. Conclusioni CD272, CD319, CD229 e CD48 sono espressi ad alta intensità dalle PC Bersagli terapeutici? Vittorio Emanuele Muccio
  • 21. Conclusioni Utili nella caratterizzazione delle PC nello studio della MRD dopo terapia con BT062 (anti-CD138) o Daratumumab (anti-CD38) Vittorio Emanuele Muccio