Minimal residual disease in multiple
myeloma by next generation sequencing
• Dr Ramon Garcia-Sanz
• 19th March 2015
MRD: The Concept
Induction
1012
TX
2TX
Consolidation
Maintenance
Relapse
1010
108
CR
106
104
MRD
102
Cure
100
METHODS FOR MRD STUDIES IN MM
Protein analysis
• Serum Electrophoresis (Palmer 1987, Bladé 1994)
• Immunofixation (Gay. 2011; Martínez 2011)
• Isoelectrofocusing (Sádaba 2004)
• Serum Free light chain assessment (Rajkumar, 2011)
Immunophenotyping
• Flow cytometry (San Miguel 2002; Paiva 2008, 2011, 2012, ; Rawstron 2002, 2013)
• Immunohistochemistry (Durie Leukemia. 2006; 20:1467)
PCR amplification of V(D)J clonal rearrangements
• CLONAL-SIZE BASED METHODs (PAGE, GeneScanning): López-Pérez 2002;
Martínez-Sánchez 2008; Martínez-López 2013)
• ALLELIC SPECIFIC OLIGONUCLEOTIDE PCR (ASO-PCR)
– Qualitative (Corradini 2000, Martinelli 2001, Ladetto 2010, Terragna 2010)
– Quantitative: ASO-RQ-PCR (Sarasquete 2006, Ladetto 2010, Terragna 2010, Puig 2013)
Identification of V(D)J clonal rearrangements by high throughput sequencing
Antigenic B-cell receptor (Immunoglobulin)
VH
IgH
IgH V
VL
IgL
H
VL
CH1
CH1
CL
CL
h
IgL
h
CH2 CH2
CH3 CH3
B-cell
Membrane
Heterodímer
Asociated to Ig
(CD79)
Inmunoglobulins
B-cell Receptor genes
Immunoglobulin heavy chain gene rearrangement
Heavy chain gene of immunoglobulin (IgH)
VH
DH
JH
Cm
Cd
Cg3
Cg1
Light chain gene of immunoglobulins (IgL-kappa)
Vk
Jk
Ck
Light chain gene of immunoglobulins (IgL-lambda
Vl
Jl1 Cl1 Jl2 Cl2 Jl3 Cl3
Jl4 Cl4
ye Ca1
Cg2
Cg4
Ce
Ca2
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DH
JH
Immunoglobulin heavy chain gene rearrangement
12
VH
23
DH
JH
Immunoglobulin heavy chain gene rearrangement
VH
DJH
Immunoglobulin heavy chain gene rearrangement
VH
DJH
Immunoglobulin heavy chain gene rearrangement
VH
DJH
Immunoglobulin heavy chain gene rearrangement
Excision circle
(signaling extremes)
Joining region (coding extremes)
Cµ
VH
DJH
Immunoglobulin heavy chain gene rearrangement
VDJH
Joining region
Cµ
VH
DJH
Immunoglobulin heavy chain gene rearrangement
CDR1
VH-FR1
CDR2
VH-FR2
CDR3
VH-FR3
JH primer
(consensus primer)
Cµ
VH VDJH
AEEFGRRSAISKWYTA
YFGH
YWYYDLV
YYUWNFNN
RVTMLE
SSTTVRWWKLEM
TTERATY
DEFTVIIP
IRACDDTMMSRRTU
ETC…
PCR analysis of IGH rearrangements
VH
VH-FR1 primers
DH
VH-FR2 primers
VH-FR3 primers
JH
JH primer
(consensus primer)
VH family primers
IGH tube A: 6 VH -FR1 primers + J consensus
IGH tube B: 7 VH-FR2 primers + J consensus
H
IGH tube C: 7 VH-FR3 primers + J consensus
DH
DH3
DH1 DH2 DH5
DH family primers
DH4
DH6 DH7
JH
JH primer
(consensus primer)
IGH tube D: 6 DHprimers + J consensus
IGH tube E: D7Hprimer + J consensus
Biomed-2, Van Dongen et al, 2003
CMN
10-1 10-2 10-3 10-4 10-5
(5-10 Healthy Donors)
101
Umbral
10-1
DRn
Copies
100
10-2
10-3
0
2
4
6
8
10
14
18
20
24
Cycles
28
34
40
44
50
Correlation of tumor cells detected by
RQ-PCR and FCM (n=103)
MRD by Flow cytometry
R = 0.881
MRD by RQ-PCR
N Puig et al, Leukemia 2013
MRD evaluation by PCR in Multiple
Myeloma patients: prognostic value
Progression free survival in patients in VGPR (n=103; 10-5, Applicability 43%)
ASO RQ-PCR rearranged of IgH genes
CMF
ASO RQ-PCR
1,0
0,8
0,6
EMR neg
n=48
EMR neg
n=56
0,4
MRD pos
n=47
p=0.003
MRDpos
n=55
0,2
p=0.001
0,0
0
12
24
36
48
60
72
84
0
12
24
36
48
60
72
84
Months from starting therapy
N Puig et al, Leukemia 2013
MRD evaluation by PCR in Multiple
Myeloma patients: prognostic value
Overal Survival patients in CR (IFX-, n=63)
ASO RQ-PCR rearranged of IgH genes
1,0
Percentage Alive
0,8
CR + MRD <10-4
n=43
0,6
CR + MRD >10-4
n=19
0,4
0,2
P = 0.008
0,0
0
1
2
3
4
5
6
7
8
Years since diagnosis
9
10
Problems ASO-RQ-PCR
• Applicability: 50%
• Sensitivity: 10-5 → (10-4)
• High specialization requirement
• Quality control
• Labor-intensive
• Cost
Multiple generations … for sequencing
1st generation
- Sanger sequencing
2nd generation (high-throughput)
- capture or amplifcation step included
- e.g. 454 (Roche), Hi-/Thru-/MiSeq (Illumina), IonTorrent PGM (Life)
3rd generation (high-throughput)
- single molecule/cell based
- e.g. Nanopore, Helicos, Pacific Bio platforms
Slide kindly provided by A.W. Langerak, Erasmus M
Different platforms for NGS - 2nd generation
454 GS Flex, Junior (Roche)
Ion Torrent , proton (Life)
HiSeq, MiSeq (Illumina)
High throughput sequencing: Is it applicable
to MRD?
Martínez-López et al, Blood 2014
IGHV1-18*01- - - - - IGHJ4-01
V-J Sequence Frequencies. The LymphoTrack Bioinformatics Software provides a stacked bar graph depicting the
relative frequencies for the 200 most common V - J rearrangements sequenced and identified in the sample.
IGHV1-18*01- - - - - IGHJ401
VH-FR2
IGHV1-12*01
IGHV1-14*01
IGHV1-18*02
IGHV1-02*02
IGHV1-03*01
IGHV1-45*02
IGHV1-67*01
IGHV1-69*01
IGHV1-69*09
IGHV2-05*01
IGHV2-70*03
IGHV3-11*01
IGHV3-13*01
IGHV3-15*01
IGHV3-19*01
IGHV3-21*01
IGHV3-23*01
IGHV3-25*01
IGHV3-30*01
IGHV3-30*13
IGHV3-32*01
IGHV3-23*01
IGHV3-33*01
IGHV3-36*02
IGHV3-37*02
IGHV3-42*01
IGHV3-43*01
IGHV3-47*01
IGHV3-23*01
IGHV3-48*01
IGHV3-49*03
IGHV3-50*03
IGHV3-23*01
IGHV3-53*01
IGHV3-54*02
IGHV3-57*01
IGHV3-57*02
IGHV3-23*01
IGHV3-06*01
IGHV3-64*05
IGHV3-65*02
IGHV3-66*04
IGHV3-71*01
IGHV3-73*01
IGHV3-23*01
IGHV3-74*02
VH-FR3
JH primer
(consensus primer)
ATTTCAGGGATTGTAGAATGAATCACATTAACAAATCTGACACAGAACTTCCTCTGAATCAATCTTTGTAAACATCAATTTCCGAATCAATGTTGTAAATAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGCAGAGTCACCATGACCAGGGACACGTCCACGAGCACAGCCTACATGGAGCTGAGCAGTCAGAGATCTGAGGACATAGATGTGTACTACTGTGCGAGACAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
ACTATGCACAGAAGCTCCAGGGCAGAGTCACCATGACCACAGACACATCCACGAGCACAGCCTACATGGAGCTGAGGAGCCTAAGATCTGACGACACGGCCGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGCAGGGTCACCATGACCAGGGACACGTCCATCAGCACAGCCTACATGGAGCTGAGCAGGCTGAGATCTGACGACACGGCCGTGTATTACTGTGCGAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCAGAGTCACCATTACCAGGGACACATCCGCGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAAGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
CAGGACAGAGTCACCATTACCAGGGACAGGTCTATGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAGGACACAGCCATGTATTACTGTGCAAGATGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GGCAGAGTCACCATGACCAGGGACACATCCACGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAAGACACGGCCATGTATTACTGTGGGAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCAGAGTCACGATTACCGCGGACGAATCCACGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
CCTGCAAGGCTTCTGGAGGCACCTTCAGCAGCTATGCTATCAGCTGGGTGCGACAGGCCCCTGGACAAGGGCTTGAGTGGATGGGAAGGATCATCCCTATCCTGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GCAGGCTCACCATCACCAAGGACACCTCCAAAAACCAGGTGGTCCTTACAATGACCAACATGGACCCTGTGGACACAGCCACATATTACTGTGCACACAGACGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
ATCTCTGAAGACCAGGCTCACCATCTCCAAGGACACCTCCAAAAACCAGGTGGTCCTTACAATGACCAACATGGACCCTGTGGACACGGCCGTGTATTACTGGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
AGGGCCGATTCACCATCTCCAGGGACAACGCCAAGAACTCACTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GGGCCGATTCACCATCTCCAGAGAAAATGCCAAGAACTCCTTGTATCTTCAAATGAACAGCCTGAGAGCCGGGGACACGGCTGTGTATTACTGTGCAAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
AGGCAGATTCACCATCTCAAGAGATGATTCAAAAAACACGCTGTATCTGCAAATGAACAGCCTGAAAACCGAGGACACAGCCGTGTATTACTGTACCACAGAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCATCATCTCCAGAGACAATTCCAGGAACTTCCTGTATCAGCAAATGAACAGCCTGAGGCCCGAGGACATGGCTGTGTATTACTGTGTGAGAAAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAACGCCAAGAACTCACTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGACCGATTCAATACCTCCAGAGATAACGCCAAGAACACACTTCATCTGCAAATGAACAGCCTGAAAACCGAGGACACGGCCCTCTATTAGTGTACCAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACAGGCTGTATCTGCAAATGAACAGCCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCAGATTCTCCATCTCCAAAGACAATGCTAAGAACTCTCTGTATCTGCAAATGAACACTCAGAGAGCTGAGGACGTGGCCGTGTATGGCTATACATAAGGTCGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GAAGGGTCGATTCACCCTCTCCAGAGATGATGCCAAGAAATCACTGTATCTGCAAATGAACAGCGTCAGAGCCGAGGATAGGTCTGTGTATTACTGTGGTGGGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
AGACACTGAAGGGTAGATTCACCATCTCTAGAGACAATGGCAAGAACATGCTGTACTTGCAAATGAACAGTCTGAGAGATGAGGACTCGGCTGTGTGAGAGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
GAAAGGCAGGTTCACCATCTCAAGAGATGATTCAAAGAACACACTGTATCTGCAAGTGAATACCCTGAAAACCGAGTACACGGCCATCTATTACTGTACTAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GCCGATTCACCATCTCCAGAGACAACAGCAAAAACTCCCTGTATCTGCAAATGAACAGTCTGAGAACTGAGGACACCGCCTTGTATTACTGTGCAAAAGATAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
ATGGGCCGATTCACCATCTCCAGAGACAACGCCAAGAAGTCCTTGTATCTTCATATGAACAGCCTGATAGCTGAGGACATGGCTGTGTATTATTGTGCAAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATGCCAAGAACTCACTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
AAGGCAGATTCACCATCTCAAGAGATGATTCCAAAAGCATCGCCTATCTGCAAATGAACAGCCTGAAAACCGAGGACACAGCCGTGTATTACTGTACTAGAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
AAGGGCCGATTGACCATCTCCAGAGACAATGCCAAGAACTCCCTCTATCTGCAAGTGAACAGCCTGAGAGCTGAGGACATGACCGTGTATTACTGTGTGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
AGGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTTCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GAGCAGATTCACCATCTCCAAAGAAAATGCCAAGAACTCACTCCGTTTGCAAATGAACAGTCTGAGAGCAGAGGGCACGGCCGTGTATTACTGTATGTGAGGGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCACAAATTAACAGTCCCAAGCGACACCTTTTCATGTGCAGTCTACCTTACAATGACCAACCTGAAAGCCAAGGACAAGGCTGTGTATTACTGTGAGGGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
TACAAATAAATTAACAGTCCCAAGCGACACCTTTTCATGTGCAGTCTACCTTACAATGACCAACCTGAAAGCCAAGGACAAGGCTGTGTATTACTGTGAGGGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATTTCCAGAGACAATACCAAAAACTCACTGTATCTGCAAATGAACAGACTGAGGGCAGAGGATGCAGCTGCATATGACTCTGTGAGAGAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGGCAGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATGTTCAAATGAGCAGTCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGTGAAAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
AGGTTTCACTAAAAACAAAACTAATCGTGGAACAACAGAATACGCCGCGTCTGTGAAAGGCAGATTCACCATCTCAAGCGATGATTCCAAAAGCATCGCCTATGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
AAGGGCAGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTTCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
AGGCAGATTCACAATCTCAAGAGATGATTCCAAAAGCATCACCTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
AAAGGCAGGTTCACCATCTCCAGAGATGATTCAAAGAACACGGCGTATCTGCAAATGAACAGCCTGAAAACCGAGGACACGGCCGTGTATTACTGTACTAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
AAGGGCCGATTCACCATCTCCAGAGACAACGCCAAGAACACGCTGTATCTGCAAATGAACAGTCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
IGHV3-18*01- - - - - IGHJ4-01
VH-FR2
IGHV1-12*01
IGHV1-14*01
IGHV1-69*01
IGHV1-02*02
IGHV1-03*01
IGHV1-45*02
IGHV1-67*01
IGHV1-69*01
IGHV1-69*09
IGHV2-05*01
IGHV2-70*03
IGHV3-11*01
IGHV3-13*01
IGHV3-15*01
IGHV3-19*01
IGHV3-21*01
IGHV3-18*01
IGHV3-25*01
IGHV3-30*01
IGHV3-30*13
IGHV3-32*01
IGHV3-18*01
IGHV3-33*01
IGHV3-36*02
IGHV3-37*02
IGHV3-42*01
IGHV3-43*01
IGHV3-47*01
IGHV3-18*01
IGHV3-48*01
IGHV3-49*03
IGHV3-50*03
IGHV3-18*01
IGHV3-53*01
IGHV3-54*02
IGHV3-57*01
IGHV3-57*02
IGHV3-23*01
IGHV3-06*01
IGHV3-64*05
IGHV3-65*02
IGHV3-66*04
IGHV3-71*01
IGHV3-73*01
IGHV3-18*01
IGHV3-74*02
VH-FR3
JH primer
(consensus primer)
ATTTCAGGGATTGTAGAATGAATCACATTAACAAATCTGACACAGAACTTCCTCTGAATCAATCTTTGTAAACATCAATTTCCGAATCAATGTTGTAAATAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGCAGAGTCACCATGACCAGGGACACGTCCACGAGCACAGCCTACATGGAGCTGAGCAGTCAGAGATCTGAGGACATAGATGTGTACTACTGTGCGAGACAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
ACTATGCACAGAAGCTCCAGGGCAGAGTCACCATGACCACAGACACATCCACGAGCACAGCCTACATGGAGCTGAGGAGCCTAAGATCTGACGACACGGCCGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGCAGGGTCACCATGACCAGGGACACGTCCATCAGCACAGCCTACATGGAGCTGAGCAGGCTGAGATCTGACGACACGGCCGTGTATTACTGTGCGAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCAGAGTCACCATTACCAGGGACACATCCGCGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAAGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
CAGGACAGAGTCACCATTACCAGGGACAGGTCTATGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAGGACACAGCCATGTATTACTGTGCAAGATGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GGCAGAGTCACCATGACCAGGGACACATCCACGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAAGACACGGCCATGTATTACTGTGGGAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCAGAGTCACGATTACCGCGGACGAATCCACGAGCACAGCCTACATGGAGCTGAGCAGCCTGAGATCTGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
CCTGCAAGGCTTCTGGAGGCACCTTCAGCAGCTATGCTATCAGCTGGGTGCGACAGGCCCCTGGACAAGGGCTTGAGTGGATGGGAAGGATCATCCCTATCCTGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GCAGGCTCACCATCACCAAGGACACCTCCAAAAACCAGGTGGTCCTTACAATGACCAACATGGACCCTGTGGACACAGCCACATATTACTGTGCACACAGACGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
ATCTCTGAAGACCAGGCTCACCATCTCCAAGGACACCTCCAAAAACCAGGTGGTCCTTACAATGACCAACATGGACCCTGTGGACACGGCCGTGTATTACTGGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
AGGGCCGATTCACCATCTCCAGGGACAACGCCAAGAACTCACTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GGGCCGATTCACCATCTCCAGAGAAAATGCCAAGAACTCCTTGTATCTTCAAATGAACAGCCTGAGAGCCGGGGACACGGCTGTGTATTACTGTGCAAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
AGGCAGATTCACCATCTCAAGAGATGATTCAAAAAACACGCTGTATCTGCAAATGAACAGCCTGAAAACCGAGGACACAGCCGTGTATTACTGTACCACAGAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCATCATCTCCAGAGACAATTCCAGGAACTTCCTGTATCAGCAAATGAACAGCCTGAGGCCCGAGGACATGGCTGTGTATTACTGTGTGAGAAAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAACGCCAAGAACTCACTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGACCGATTCAATACCTCCAGAGATAACGCCAAGAACACACTTCATCTGCAAATGAACAGCCTGAAAACCGAGGACACGGCCCTCTATTAGTGTACCAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACAGGCTGTATCTGCAAATGAACAGCCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCAGATTCTCCATCTCCAAAGACAATGCTAAGAACTCTCTGTATCTGCAAATGAACACTCAGAGAGCTGAGGACGTGGCCGTGTATGGCTATACATAAGGTCGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GAAGGGTCGATTCACCCTCTCCAGAGATGATGCCAAGAAATCACTGTATCTGCAAATGAACAGCGTCAGAGCCGAGGATAGGTCTGTGTATTACTGTGGTGGGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
AGACACTGAAGGGTAGATTCACCATCTCTAGAGACAATGGCAAGAACATGCTGTACTTGCAAATGAACAGTCTGAGAGATGAGGACTCGGCTGTGTGAGAGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
GAAAGGCAGGTTCACCATCTCAAGAGATGATTCAAAGAACACACTGTATCTGCAAGTGAATACCCTGAAAACCGAGTACACGGCCATCTATTACTGTACTAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GCCGATTCACCATCTCCAGAGACAACAGCAAAAACTCCCTGTATCTGCAAATGAACAGTCTGAGAACTGAGGACACCGCCTTGTATTACTGTGCAAAAGATAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
ATGGGCCGATTCACCATCTCCAGAGACAACGCCAAGAAGTCCTTGTATCTTCATATGAACAGCCTGATAGCTGAGGACATGGCTGTGTATTATTGTGCAAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATCTCCAGAGACAATGCCAAGAACTCACTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
AAGGCAGATTCACCATCTCAAGAGATGATTCCAAAAGCATCGCCTATCTGCAAATGAACAGCCTGAAAACCGAGGACACAGCCGTGTATTACTGTACTAGAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
AAGGGCCGATTGACCATCTCCAGAGACAATGCCAAGAACTCCCTCTATCTGCAAGTGAACAGCCTGAGAGCTGAGGACATGACCGTGTATTACTGTGTGAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
AGGGCCGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTTCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GAGCAGATTCACCATCTCCAAAGAAAATGCCAAGAACTCACTCCGTTTGCAAATGAACAGTCTGAGAGCAGAGGGCACGGCCGTGTATTACTGTATGTGAGGGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
GGGCACAAATTAACAGTCCCAAGCGACACCTTTTCATGTGCAGTCTACCTTACAATGACCAACCTGAAAGCCAAGGACAAGGCTGTGTATTACTGTGAGGGAGGGGCCGTGGCACCCTGGTCACTGTCTCCTCAG
TACAAATAAATTAACAGTCCCAAGCGACACCTTTTCATGTGCAGTCTACCTTACAATGACCAACCTGAAAGCCAAGGACAAGGCTGTGTATTACTGTGAGGGAGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
GGGCCGATTCACCATTTCCAGAGACAATACCAAAAACTCACTGTATCTGCAAATGAACAGACTGAGGGCAGAGGATGCAGCTGCATATGACTCTGTGAGAGAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
GGGCAGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATGTTCAAATGAGCAGTCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGTGAAAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
AGGTTTCACTAAAAACAAAACTAATCGTGGAACAACAGAATACGCCGCGTCTGTGAAAGGCAGATTCACCATCTCAAGCGATGATTCCAAAAGCATCGCCTATGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
AAGGGCAGATTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTTCAAATGAACAGCCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCGAGAGGGGCAAAGGGACCACGGTCACCGTCTCCTCAG
AGGCAGATTCACAATCTCAAGAGATGATTCCAAAAGCATCACCTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTGTATTACTGTGCGAGAGAGGGGCCAGGGAACCCTGGTCACCGTCTCCTCAG
AAAGGCAGGTTCACCATCTCCAGAGATGATTCAAAGAACACGGCGTATCTGCAAATGAACAGCCTGAAAACCGAGGACACGGCCGTGTATTACTGTACTAGAGGGGCCAGGGCACCCTGGTCACCGTCTCCTCAG
GGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
AAGGGCCGATTCACCATCTCCAGAGACAACGCCAAGAACACGCTGTATCTGCAAATGAACAGTCTGAGAGCCGAGGACACGGCTGTGTATTACTGTGCAAGAGGGGCCAAGGAACCCTGGTCACCGTCTCCTCAG
MRD evaluation by HTS in Multiple
Myeloma patients: clinical value
Deep sequencing of rearranged BCR genes (Lymphosight™)
N 133 cases in CR or VGPR (sensitivity ≥10-5), GEM00,05,10; Applicability 91%
HTS vs. FCM
• 62/101 (63%) samples were
positive with both
techniques
• 22/101 (22%) samples were
negative with two
techniques
• 17/101 (17%) were
discordant:
• FCM+SEQ-: 5
• FCM-SEQ+: 12
Martinez-Lopez et al , Blood 2014
Clinical value of MRD evalauted by
sequencig in MM patients with MM
Deep sequencing by Ig rearrangement (LymphoSight™)
N 110 cases in CR or VGPR (sensitivity ≥10-5)
N 62 cases in sCR (sensitivity ≥10-5)
Percentage alive
Months
Applicabiliity 91%
Time to tumor progression (Only CR)
Alive without progrression
Overall survival (all patients)
Months
Martínez-López et al, Blood 2014
Comparison of different methodologies
ASO PCR of BCR
genes
HTS of BCR
genes
Flow
Cytometry
10-5-10-6
10-5-10-6
10-4-10-5
Low
High
Very High
Time-consuming
Very High
Very High
High
Specific reagents
Yes
No
No
300 €
900 €
150 €
No
Yes*
No**
Expertise
Very High
Very High
Very High
Availability
Low
Low
High
Sensitivity
Applicability
Cost
Clonal evolution detectable
*No clonal evolution has been shown in MM at the BCR gene rearrangement;
**FCM can detect aberrant PC subsets with an Ag profile different to diagnosis
Future
Technology
Problem
Solution
FCM
Sensitivity
Increase the input cells (107 cells)
Specificity
Go up to 8 colors
Expertise requirement New software
ASO-PCR
Sensitivity
Applicability
Expertise requirement
Time consuming, cost
Increase input DNA (6 mcg, 106 cells)
Discard SC, use DCT method
Standardization
Optimization
HTS
Sensitivity
Applicability
Expertise requirement
Time consuming, cost
Availability
Increase input DNA (6-60mcg, 106-107cells)
Increase targets (mutations)
New software
Optimization
Competition; Lymphosight™, Lymphotrack™,
Euroclonality/EuroNGS
Clinical validation in Prospective Studies
Conclusions
• MRD detection by molecular technology is applicable to MM patients
rendering similar results or even superior to FCM
• MRD detection by NGS is an useful method for stratifying patients
and can be used to assess molecular response in MM
• With this methodology, today it is posible to go close to
personalized therapeutic strategies:
• MRD (‒): treatment reduction
• MRD (+): treatment increase or continuous therapy
Molecular Laboratory Team
Carmen Chillón
Ana Balanzategui
M. Eugenia Sarasquete
Miguel Alcoceba
Elena Sebastián
Cristina Jiménez
Isabel López
María García
Marcos González
Ramón García-Sanz
Luis Marín
Rocío Corral
Myeloma Team
Ramón García Sanz
Norma C. Gutiérrez
Enrique M. Ocio
M. Victoria Mateos
Noemí Puig
Grupo Español de Mieloma (GEM)
Hospitales
Clínico de Barcelona
12 Octubre (Madrid)
Clínico de Salamanca
Clínico de San Carlos (Madrid)
Hospital de Badalona
Clínico de Asturias
Fr. Peset (Valencia)
Universitario de Canarias
Rio Ortega (Valladolid)
Cínico de Zaragoza
Hospital General de Jerez
Ramón y Cajal (Madrid)
Morales Meseguer (Murcia)
La Fe (Valencia)
C.U. de Navarra
Galdakao (Vizcaya)
Clínico de Valladolid
Sant Pau (Barcelona)
Arnau Vilanova (Lérida)
Universitario de Santiago
General Universitario de Valencia
Universitario de Getafe (Madrid)
Insular de las Palmas
H. de La Princesa (Madrid)
Severo Ochoa (Madrid)
Juan XIII (Tarragona)
Toledo
Gandía (Valencia)
Vall D´Hebrón (Barcelona)
San Jorge (Huesca)
Verge de la Cinta (Tortosa)
Alarcos (Ciudad Real)
Mataró (Madrid)
Juán Canalejo (Coruña)
Ferrol
Salamanca Group: Puig, Vidriales, Sarasquete, Gutierrez,
Mateos, Jinénez, Orfão, González. (Paiva, San Miguel)
Madrid (12O) Group: Lahuerta, Martínez-López,
Montalbán, MA Montalban, Martin, Fernandez
Hospitales
General de Segovia
Cruces (Bilbao)
St. Coloma de Gramanet
(Barcelona)
Gregorio Marañon (Madrid)
Carlos Haya (Málaga)
H. Tauli (Gerona)
Huesca
Palencia
Alcira (Valencia)
H. Del Mar (Barcelona)
Mahón (Baleares)
Clínico de Málaga
Xeral Cies (Vigo)
Plasencia
Cáceres
Algeciras
Ávila
Jaén
S. Pau i Sta Tecla
(Tarragona)
General de Guadalajara
Sagunto (Valencia)
Son Dureta (Mallorca)
Cuenca
Alicante SUS
M. Valdecilla (Santander)
Albacete
H. Del Bierzo
Fundación Jiménez Díaz
(Madrid)
Elda (Alicante)
V. Del Rosel (Cartagena)
Castellón
Mutua Tarrasa
Consorcio Tarrasa
C. Corachán (Barcelona)
Descargar

Dr Ramon Garcia-Sanz