The impact of ultra-high resolution HLA typing on ...ebmt.co.uk/wp-content/uploads/2018/05/Mayor_EBMT... · –NEG:Ambiguous meaning of allele level resolution –NEG: Multiple HLA

The impact of ultra-high resolution HLA typing on

unrelated donor HSCT outcome – Does NGS typing

make a difference?Dr Neema Mayor Head of Immunogenetics Research, Anthony Nolan Research InstituteHonorary Lecturer, UCL Cancer Institute

ACKNOWLEDGEMENTS

ALL OF YOU!

Genetics:HLA

Genetics:Non- HLA

Clinical Factors(donor age, CMV etc.)

SuccessfulHSCT

What makes the perfect match?

0

50

100

150

200

250

300

350

400

19961997

19981999

20002001

20022003

20042005

20062007

20082009

20102011

20122013

20142015

20162017

2018

No. S

ampl

es

Year

Patient/Donor Project Progress

Jan-Aug

Patient samples returned

Donor samples returned

Anthony Nolan Patient/Donor Project

• Project Aims: What makes the perfect match?

1. To use high resolution HLA typing methods to identify HLA

mismatches that were not reported when using standard typing

methods

2. To identify how known and unknown HLA mismatches impact on

UD-HSCT outcome

3. To determine the impact of HLA-DPB1 matching on UD-HSCT

outcome

4. To identify novel genetic factors that impact on UD-HSCT outcome

5. To determine how clinical factors (e.g. donor age, CMV matching

etc.) affects outcome

HLA ALLELE MATCHING ON OS

Lee SJ et al. Blood (2007) 110(13):4576-4583

Time (years)543210

% O

ve

rall S

urv

iva

l

100

90

80

70

60

50

40

30

20

10

0

Page 1

HLA ALLELE MATCHING ON OVERALL SURVIVAL

10/10 match (n=933)

9/10 match (n=254)

≤8/10 match (n=84)

Shaw BE et al. BMT (2017) 52:717-725

N=1271P<0.001

Impact of HLA-DPB1 matching on OS

Years post HCT

12/12 match (n=1216)

10/10, DP permissive mm

(n=2539)

10/10, DP non-permissive mm

(n=1654)

12/12 vs non-permissive mm P=0.002

Fleischhauer K et al. Lancet Oncology(2012) 13(4):366-374

1

L

exon

proteindomain

5

TM

8

3'UT

6 7

CYT

2 3 4

a2 a3a1

HLA class I moleculePeptide

Variation along HLA-BExon 1

Exon 2

Exon 3

Exon 4

Exon 5

Exon 6 Exon 7

HLA is Hyperpolymorphic!

CLASS IHLA-A 4,340HLA-B 5,212HLA-C 3,930

CLASS IIHLA-DRB1 2,268HLA-DQB1 1,257HLA-DPB1 1,014

The HLA dilemma• Allelic level typing:

– POS: Improves survival and reduces risk of complications– POS: Decreases time for donor selection– POS: Anthony Nolan phenotype project - >50x more likely to be chosen

• Pre-NGS high-throughput methodologies– NEG: Ambiguous meaning of allele level resolution– NEG: Multiple HLA typing methods and cross-referencing results– NEG: Time and financial implications– NEG: Limitations in resolving all ambiguity– NEG: Bioinformatics of storing data, additional ambiguity, costs

• Ideal scenario:– Definitive allelic level resolution typing– One method– Quicker

HLA genes – The benefit of TGS

HLA-A2 3 4

HLA-B2 3 4

HLA-C2 3 4

Class I

3.5 KB

Class II

HLA-DRB12 3

HLA-DQB12 3

HLA-DPB12 3

6.5-16 KB

The long read lengths enabled by TGS sequencing allows us to accurately and definitively phase polymorphisms over regions that could cover entire genes

TGS typing at Anthony NolanSMRT Bell Adaptors

SMRT DNA sequencingContinuous Long Read (CLR) orPolymerase Read

Sub-read sequences

Double-stranded PCR amplicon – Person 1

Double-stranded PCR amplicon – Person 2

Ligation

Person 1 Person 2

Anthony Nolan’s ultra-high resolution HLA typing strategy

• Full-length HLA Class I genes amplified using an in-house method

• HLA-A gene ~3.5kb

• HLA-B and -C amplicons ~3.3 kb

• Near full-length Class II genes amplified using an in-house method

• HLA-DRB1 ~4 kb (exons 2 and 3)

• HLA-DPB1 amplicons ~5.5 kb (exons 2, 3 and 4)

• HLA-DQB1 amplicons ~4.5 kb (exons 2, 3, 4 and 5)

1 54

DRB1

2 65� UTR 3� UTR3

DPB1 DQB1

1 5432 65� UTR 3� UTR87

Does this additional variation matter?

Cohort Characteristics

• 891 UD-HSCT donor/recipient pairs typed by TGS

– Transplanted between 1996-2011, UK transplant centre

– Adult and paediatric recipients with haematological malignancy

• median patient age: 41.4y (1.1-71.9)

• 25.1% AML, 18.4% ALL, 17.2 % MDS, 13.1% CML, 11.1% NHL, 15.1% Other

– 81.4% T-cell depletion (in vivo alemtuzumab; 13% missing data)

– 54.1% PBSC, 45.1% BM

– EBMT risk score: 45.6% Good, 36.5% intermediate, 15.1% poor

– 51.2% Myeloablative Conditioning, 46.6 % RIC

• Typing and matching strategy for this study:

– HLA class I: Full gene sequencing

– HLA class II: CDS typing, covers all exons that encode the expressed extracellular

domains of the mature protein

UHR typing matching status, n (%)

5/12 6/12 7/12 8/12 9/12 10/12 11/12 12/12 Total

Pre

vio

us

HL

A m

atc

hin

g s

tatu

s

12/120(0)

0(0)

0(0)

0(0)

1(1.0)

5(5.1)

17(17.2)

76(76.8)

99(100)

11/120(0)

0(0)

0(0)

4(1)

14(3.6)

68(17.6)

297(76.7)

4(1.0)

387(100)

10/120(0)

0(0)

1(0.3)

14(4.8)

70(23.8)

198(67.3)

10(3.4)

1(0.3)

294(100)

9/121(1.1)

2(2.2)

10(11.0)

24(26.4)

47(51.6)

5(5.5)

2(2.2)

0(0)

91(100)

8/120(0)

2(16.7)

1(8.3)

8(66.7)

1(8.3)

0(0)

0(0)

0(0)

12(100)

<8/120(0)

3(37.5)

4(50.0)

1(12.5)

0(0)

0(0)

0(0)

0(0)

8(100)

Overall1

(0.1)

7

(0.8)

16

(1.8)

51

(5.7)

133

(14.9)

276

(30.9)

327

(36.6)

81

(9.1)

891

(100)

Results: Impact of Ultra-High Resolution (UHR) HLA

typing on HLA matching status


5/12 6/12 7/12 8/12 9/12 10/12 11/12 12/12 Total

Pre

vio

us

HL

A m

atc

hin

g s

tatu

s

12/120(0)

0(0)

0(0)

0(0)

1(1.0)

5(5.1)

17(17.2)

76(76.8)

99(100)

11/120(0)

0(0)

0(0)

4(1)

14(3.6)

68(17.6)

297(76.7)

4(1.0)

387(100)

10/120(0)

0(0)

1(0.3)

14(4.8)

70(23.8)

198(67.3)

10(3.4)

1(0.3)

294(100)

9/121(1.1)

2(2.2)

10(11.0)

24(26.4)

47(51.6)

5(5.5)

2(2.2)

0(0)

91(100)

8/120(0)

2(16.7)

1(8.3)

8(66.7)

1(8.3)

0(0)

0(0)

0(0)

12(100)

<8/120(0)

3(37.5)

4(50.0)

1(12.5)

0(0)

0(0)

0(0)

0(0)

8(100)

Overall1

(0.1)

7

(0.8)

16

(1.8)

51

(5.7)

133

(14.9)

276

(30.9)

327

(36.6)

81

(9.1)

891

(100)




5/12 6/12 7/12 8/12 9/12 10/12 11/12 12/12 Total

Pre

vio

us

HL

A m

atc

hin

g s

tatu

s

12/120(0)

0(0)

0(0)

0(0)

1(1.0)

5(5.1)

17(17.2)

76(76.8)

99(100)

11/120(0)

0(0)

0(0)

4(1)

14(3.6)

68(17.6)

297(76.7)

4(1.0)

387(100)

10/120(0)

0(0)

1(0.3)

14(4.8)

70(23.8)

198(67.3)

10(3.4)

1(0.3)

294(100)

9/121(1.1)

2(2.2)

10(11.0)

24(26.4)

47(51.6)

5(5.5)

2(2.2)

0(0)

91(100)

8/120(0)

2(16.7)

1(8.3)

8(66.7)

1(8.3)

0(0)

0(0)

0(0)

12(100)

<8/120(0)

3(37.5)

4(50.0)

1(12.5)

0(0)

0(0)

0(0)

0(0)

8(100)

Overall1

(0.1)

7

(0.8)

16

(1.8)

51

(5.7)

133

(14.9)

276

(30.9)

327

(36.6)

81

(9.1)

891

(100)



Results: impact of UHR HLA typing on OS

Time (years)5.04.03.02.01.0.0

Prob

abili

ty o

f Sur

viva

l

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Page 1

UHR 12/12 HLA match (n=76)

Previous 12/12 HLA match (n=23)

P=0.022N=99

5 year OS:UHR 12/12 54.8%Previous 12/12 30.1%

Time (years)5.04.03.02.01.0.0

Pro

babi

lity

of S

urvi

val

1.0

0.8

0.6

0.4

0.2

0.0

Page 1


Coding 12/12 HLA match (intronic/UTR differences only; n=13)

P=0.169N=94

One year OS (y):TGS 12/12 75.2%Coding 12/12 53.8%

Results: impact of intronic/UTR variation OS

E.g. A*02:01:01:01 vs A*02:01:01:02

One year OS (y):TGS 12/12 75.2%Coding 12/12 53.8%

Results: impact of intronic/UTR variation OS


All other mismatches (n=797)

P=0.02N=891

Coding 12/12 HLA match (intronic/UTR differences

only; n=13)

Clinical impact of intronic/UTR variation?

Petersdorf et al. PLOS medicine (2007) 4(1):59-68

Prob

abili

ty o

f aG

vHD

gr 3

-4

Impact of UHR HLA typing on OS – MV analysis

Time (years)5.04.03.02.01.0.0

Prob

abili

ty o

f Sur

viva

l

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Page 1


UHR 10/10 + DP TCED (n=192)

UHR 10/10 + DP TCEM (n=219)

Co-variables: Patient age, era, EBMT risk score, CMV matching

HR 1.281, P=N/S

Key:DP TCEM = DP permissive mm

DP TCED = DP non-permissive mm

Impact of UHR HLA typing on OS – MV analysis

Time (years)5.04.03.02.01.0.0

Prob

abili

ty o

f Sur

viva

l

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Page 1


UHR 10/10 + DP TCED (n=192)

UHR 10/10 + DP TCEM (n=219)

Co-variables: Patient age, era, EBMT risk score, CMV matching

Key:DP TCEM = DP permissive mm

DP TCED = DP non-permissive mm

HR 1.984, P=0.001

Time (months)12.0010.008.006.004.002.00.00

Pro

bab

ility

of

NR

M

1 .0

0.8

0.6

0.4

0.2

0.0

Page 1

Non-relapse mortality


UHR 10/10 + DP TCED(n=211)

UHR 10/10 + DP TCEM (n=231)

P=0.051N=523

12 Month NRM:12/12 16.8%10/10 + TCEM 19.7%10/10 + TCED 29.9%

MV: TGS 12/12 M Vs

10/10 + DP TCEDHR: 1.832P=0.071

Acute GvHD

aGvHD12/12 UHR

match

10/10 + DP

TCEM

10/10 + DP

TCED

Total

Grade 0-164

(84.2)162

(73.3)144

(70.6)370

(73.9)

Grade 2-412

(15.8)59

(26.7)60

(29.4)131

(26.1)

Overall76

(100)

221

(100)

204

(100)

501(100)

UV P=0.068

MV: Overall P=0.062 but

12/12 vs 10/10 DP TCEM: OR 1.98 (0.98-4.0), P=0.059

12/12 vs 10/10 DP TCED: OR 2.37 (1.2-4.9), P=0.018

Disease relapse

Time (years)5.004.003.002.001.00.00

Pro

babi

lity

of R

elap

se

1 .0

0.8

0.6

0.4

0.2

0.0

Page 1


UHR 10/10 + DP TCED (n=205)

UHR 10/10 + DP TCEM (n=227)

P=0.73N=509

UHR HLA typing & CMV matching on OS – MV

Co-variables: Patient age, era,

EBMT risk score

Time (years)5.04.03.02.01.0.0

Prob

abili

ty o

f Sur

viva

l

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Page 1

A

N=487

BCDE

F

A: 12/12 + CMV M (n=64)

B: 10/10 TCEM + CMV M (n=167)

C: 10/10 TCEM + CMV mM (n=142)

D: 12/12 + CMV mM (n=13)

E: 10/10 TCED + CMV M (n=52)

F: 10/10 TCED + CMV mM (n=50)

A v B: HR 1.472, P=0.118

A v C: HR 1.605, P=0.100

A v D: HR 1.823, P=0.151


Co-variables: Patient age, era, EBMT risk score

Time (years)5.04.03.02.01.0.0

Prob

abili

ty o

f Sur

viva

l

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Page 1

A

N=487

BCDE

F

A: 12/12 + CMV M (n=64)B: 10/10 TCEM + CMV M (n=167)C: 10/10 TCEM + CMV mM (n=142)D: 12/12 + CMV mM (n=13)E: 10/10 TCED + CMV M (n=52)F: 10/10 TCED + CMV mM (n=50)

A: 12/12 + CMV M vs

E: 10/10 TCED + CMV MHR 2.03 (1.02-3.30)

P=0.004


Co-variables: Patient age, era, EBMT risk score

Time (years)5.04.03.02.01.0.0

Prob

abili

ty o

f Sur

viva

l

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Page 1

A

N=487

BCDE

F

A: 12/12 + CMV M (n=64)B: 10/10 TCEM + CMV M (n=167)C: 10/10 TCEM + CMV mM (n=142)D: 12/12 + CMV mM (n=13)E: 10/10 TCED + CMV M (n=52)F: 10/10 TCED + CMV mM (n=50)

A: 12/12 + CMV M vs

F: 10/10 TCED + CMV mMHR 3.25 (1.90-5.55)

P< 0.0001

5yr OSA: 62.5%F: 17.5%

• TGS HLA typing identified that 24% of previously typed 10/10 matched pairs had unknown

mismatches (25% of 12/12 matched pairs)

• HLA typing Laboratories providing HCT services need to be able to type and match patients and donors at this level of resolution because it results in significant survival advantages:

– 12/12 TGS match is the best possible donor option

– 10/10 TGS HLA + DPB1 TCE permissively mismatched donor – N/S differences

– Avoid DPB1 non-permissively mismatched donors

– Observed 45% difference in survival probability in 10/10 TGS matched pairs

depending on TGS HLA typing, -DPB1 TCE and CMV matching

Does ultra-high resolution HLA typing make a difference? – YES!

ACKNOWLEDGEMENTS

Anthony NolanProf Steven MarshProf Alejandro MadrigalHenny Braund

James HayhurstDr Thomas TurnerWill Bultitude

Dr Richard SzydloDr Chloe AnthiasJames Robinson

Dr Katy LathamJexray SaynoFranco Tavarozzi

BSBMTJulia PerryMarie Wilson

All UK Transplant & Harvest centres

All Patients & Donors who consented to be part of the study

Documents

The impact of ultra-high resolution HLA typing on ...ebmt.co.uk/wp-content/uploads/2018/05/Mayor_EBMT... · –NEG:Ambiguous meaning of allele level resolution –NEG: Multiple HLA