HLA に関する資料集
医 師 の 方 へ2007 年 10 月 12 日
財団法人骨髄移植推進財団

目次
１．ドナー検索時の評価点

P. 2

２．患者の HLA 抗原と検索されるドナーの HLA 抗原

P. 3

３．ドナーの確認検査とコーディネートの流れ

P. 4

４．HLA に関する詳細説明

P. 5

５．検査方法P. 6

６．その他 ドナー検索に関する参考情報

P. 8
P. 9

７．HLA 適合度をみる場合の判断例
８．SBT 法による確定アリルと蛍光ビーズ法による高頻度アリルの比較表

P. 10

９．解析資料集 / 目次

P. 13

重症 GVHD ハイリスクな HLA 型の組み合わせについて

P. 14

非血縁者間骨髄移植における HLA-C 適合度の解析

P. 16

HLA 適合度に基づいた治療成績の分析

P. 18

High-risk HLA allele mismatch combinations responsible for severe acute
P. 20
graft-versus-host disease and implication for its molecular mechanism
T 細胞非除去秘訣縁者間骨髄移植を受けた白血病患者における HLA 型と P. 27
KIR リガンド適合度の臨床成績への影響について
Effects of HLA Allele and Killer Immunoglobulin-Like Receptor Ligand P. 28
Matching on Clinical Outcome in Leukemia Parients UndergoingTransplantation With T-cell-Replete Marrow From an Unrelated Donor
ミスマッチ症例における急性 GVHD Grade3-4 発症率

P.42

コーディネート過程において、適切なドナーを早い段階で選択することが、迅速な移植を実現する上で重要な鍵の一つとなっております。この度、ドナー選択に役立てていただきたい資料を一冊にまとめましたので、どうぞご活用ください。＊過去に配布済みの資料については当時の日付にて掲載しております。
なお、ドナー選択には患者さんのアリルデータが欠かせません。患者確認検査は登録後すぐに実施願います。化学療法中で白血球数が不足している、近日中の外来予定がないなど、採血までに日数を要する場合にはお問い合わせください。
お問い合わせ先：移植調整部 TEL03-5280-4771／FAX03-5280-3856

1

1. ドナー検索時の評価点
ドナーは評価点に基づき優先順位が付けられ検索されます。
評価点は解析結果をもとに、点数配分されています。

1-1. ランク評価点
ランク

評価点

6 抗原マッチ
DR ミスマッチ

400,000
300,000

B ミスマッチ

200,000

A ミスマッチ

100,000＊ 現在、C 座の血清ミスマッチに関してはランク評価点がありません。
＊ ただし、アリルが判明している場合は下記のように評価対象となります。

1-2. HLA 型評価点
HLA-A

HLA-B

HLA-DR

HLA-C

アリルマッチ(抗原ごと)

700

700

100

200

コードマッチ(抗原ごと)

650

650

50

150

抗原マッチ

0

アリルミスマッチ(ローカスごと)-24,000-24,000-8,000-12,000

抗原ミスマッチ0

血清型 split match30

1-3. その他評価点
ランク

評価点

血液型 ABO 一致

4

血液型 Rh 一致3

体重比率120% ＜ 3

性別一致

0

年齢
居住地域

20〜29 歳：2
30〜39 歳：10

1-4.ドナープールの階層状況と HLA 型評価点
対象ドナー
血清フルマッチ

A､B､DR 3 ローカス全て
スプリットマッチなら 30 点加算(患者が血清のみの場合)ドナーの HLA
アリル 4 桁 判明
血清 2 桁のみ（アリル未検査）
アリル 4 桁 判明

〜血清フルマッチを例として〜
アリルの適合度
A,B,C,DR アリルフルマッチ
不明
ＤＲ１アリルミスマッチ
・中略
・
A,B,C,DR４座 8 抗原全て
アリルミスマッチ

評価点①403,400②400,000③395,300
・
中略・④332,000

ミスマッチ検索対象ドナーについても、同様に、マッチなら加点、ミスマッチなら減点され、順位が決まります。

22. 患者の HLA 抗原と検索されるドナーの HLA 抗原
ブロード抗原とスプリット抗原

Broad specificities
A10
A19
A2
A28
A9
B12
B14
B15
B16
B17
B21
B22
B27
B40
B5
B7
B70
C3
DR1
DR2
DR3
DR5
DR6
DQ1
DQ3

Split and associated antigens#
A25, A26, A34, A66
A29, A30, A31, A32, A33, A74
A203#, A210#
A68, A69
A23, A24, A2403#
B44,B45
B64,B65
B62,B63,B75,B76,B77
B38,B39,B3901#,,B3902#
B57,B58
B49,B50,B4005#
B54,B55,B56
B2708#
B60,B61
B51,B52,B5102#,B5103#
B703#
B71,B72
C9, C10
DR103#
DR15, DR16
DR17, DR18
DR11, DR12
DR13, DR14, DR1403#, DR1404#
DQ5, DQ6
DQ7, DQ8, DQ9(WHO Nomenclature for Factors of the HLA System, 1996 より)

実際の例
患者の
抗原

検索されるドナーの抗原
スプリット

B16

B38
B39

B3901

B3902

DR2

B38
B39

B3901

B3902

ブロード
B16
B38
B39
B3901
B3902
B16
B3901
B3902
B16
B39
B16
B3902
B39
B16
B3901
DR2
DR15
DR16

患者の
抗原

検索されるドナーの抗原
スプリット

DR5

DR6

DR11
DR12
DR13
DR14

DR1404

DR15
DR16

DR11
DR12
DR13
DR14

DR1404

DR15
DR16

3

ブロード
DR5
DR11
DR12
DR6
DR13
DR14
DR1403
DR1404
DR5
DR5
DR6
DR6
DR1403
DR1404DR6
DR14DR1403
DR2
DR2

例 1 患者 HLA-DR2 で検索する場合↓
HLA-DR2／DR15／DR16 のドナーが検索されます

例 2 患者 HLA-DR15 で検索する場合↓
HLA-DR2／DR15 のドナーが検索されます(HLA-DR16 は検索されません)3. ドナーの確認検査とコーディネートの流れドナーが検索された時点で保持している HLA データによって、ドナー確認検査の検査項目が異なります。

ドナー検索時のHLA データ

Ⅰドナー

Ⅱドナー

Ⅲドナー

☆ドナー

全体の 52％
血清型 または
一部のアリル

全体の 36％
NMDP コードと高頻度アリル

全体の 4％NMDP コードと高頻度アリルまたは
確定アリル

全体の 8％
前回スクリーニング
から 180 日以内に再びコーディネート
を開始したドナー(2005 年 3 月以降に登録し、本人確認検査が未済みのドナー)

HLA 検査スクリーニングのみ

スクリーニングのみ(蛍光ﾋﾞｰｽﾞ法)

の場合あり

ドナー
確認検査

確認検査省略可スクリーニング

無 料

ドナー選定〜
最終同意面談希望により、SBT 法 HLA オプション検査
予約は確認検査以降いつでも受け付けます（例えば Cw 検査結果を見てから 1 位ドナーを決めるなども可能です）

希望により、
SBT 法 HLA
オプション検査

Ⅰ・Ⅱ・Ⅲ・☆ドナーの％は 2006/10〜2007/3 に検索されたドナーを全体数としたデータです。

3-1. SBT 法による HLA オプション検査① SBT 法 HLA 検査を実施するかどうかは、蛍光ビーズ法 HLA 検査結果が判明した後に、「蛍光ビーズ法による高頻度アリルと SBT 法による確定アリルの比較表」(P.10〜12 参照)を参照するなどして、高頻度アリルの意
味をよくご理解いただいた上で、担当医師がご判断ください。現時点のデータでは、高頻度アリルと確定アリ
ルは 99％以上の確率で一致しています。
② SBT 法 HLA 検査は HLA-A、B、DRB1 の他に、C、DP.B1、DQB1 も受付けております。高頻度アリルの結果を見た上で、さらに高精度の検査(SBT 法)をご希望の場合はご連絡ください。
③ スクリーニング検査時に採血した残検体を使用するため、ドナーの方から改めて採血する必要はありません。
④ SBT 法 HLA 検査は有料(患者負担)です。

4

4. HLA に関する詳細説明

4-1. HLA 検査結果レベル
HLA 検査で出される結果のレベルは、検査方法・試薬によって決定されます。下表は検査で 出された結果の例です。
A locus
血清学的検査DNA 検査SBT 法 はこのレベル

ブロード抗原
スプリット抗原
Low
Resolution

B locus

DR locus

A19
A31

B40
B61

DR5
DR11

A＊31

B＊40

DRB1＊11

MiddleResolution

A＊3101/3102

B＊4001/4006/4009

DRB1＊1101/1104/1105/1106

High
Resolution

A＊3101

B＊4006

DRB1＊1104「 / (スラッシュ)」は「または」の意

蛍光ビーズ法は
このレベル4-2. 用語説明
血清対応型

検査の結果得られた DNA 型について対応する血清型。

確定アリル

SBT 法で検査した結果。

NMDP コード

アリルの組み合わせをアルファベットで コード化したもの。Middle Resolution レベル。
NMDP が定義し世界各国で使用。
(システム構築が完了するまでは、表記されません。)

高頻度アリル

確定したアリルではない。NMDP コードで表記したアリルのなかで、日本人に最も高頻度に見られるアリル。
日本人で 0.1%以下の頻度で存在するアリルは無視した上で 4 桁表記したもの。

座（ローカス）と抗原

HLA の適合度を表現する際に「１座不一致」、「２座不一致」ということをみかけますが、これは正確な表現法ではありません。「座」とは遺伝子座、つまり A 座、B 座、DR 座などを意味します。
HLA の適合度については「抗原の不一致」なのか「アリルの不一致」なのかを明確にして表現する必要があります。抗原での表現法を例に取ってみると、「１座不一致」といっても同一遺伝子座では２つの抗原がありますので、一方のみが不一致である「１抗原不一致」と両方が不一致である「２抗原不一致」の場合があります。「２座不一致」では２〜４抗原不一致までが含まれることになります。

HLA 検査の結果は、4 つ(血清型･確定アリル･NMDP コード･高頻度アリル)に分類して表示します。

55. 検査方法

5-1. 蛍光ビーズ法(PCR-rsso 法)
蛍 光 ビ ー ズ 法 で は 、 多 く の 場 合 ア リ ル (DNA) デ ー タ を １ つ に 特 定 す るこ とは で きま せ ん が、 検 査 結 果 はNMDP コードで表記し、可能性があるアリルを絞り込むことが可能です。
NMDP コードNMDP コードの要素 (可能性があるアリル)

高頻度アリル

例 1)
DRB1＊01EW

DRB1＊0101/05/07/08/11

0101

例 2)
DRB1＊15GEPDRB1＊1501/06/13

1501＊ NMDP コードが意味する具体的なアリルは、NMDP のホームページにある “NMDP Allele Code List“ でご覧になれます。
URL ： http://bioinformatics.nmdp.org/HLA/allele_code_lists.html＊ 各コードの要素は次ページ Lookup Tool をご利用ください
URL ： http://bioinformatics.nmdp.org/cgi-bin/HLA/ALLELE/dnatyp.pl5-2. SBT 法High resolution レベルの DNA タイピングで、遺伝子の塩基配列を幅広く解析するため、非常に精密な測定が可能です。

5-3. コード検索の例＜B75（B1507）を持つ患者さんに B62(高頻度アリル：1501)を持つドナーが検索される理由＞
高頻度アリル：B1501、血清対応型：B62（NMDP コード：B15BNUF）のドナーがコードマッチドナーとして上位に検索される場合があります。これは、次のような仕組みによります。
ドナーの HLA 検査（蛍光ビーズ法）の結果である B15BNUF は、NMDP コードの要素として次ページに示すとおり、1501/1507・・など 31 種類のアリルの可能性を持ちます。そのうち日本人と仮定した場合に最も高頻度で見られるアリルは B1501（血清対応型 B62）で高頻度アリルとしています。このとき、31 種類のアリルは B15BNUFのコードマッチとして評価されるため全て同等であり、高頻度アリル B1501 を特別に高く評価はしておりません。

6

5-4. DNA Type Lookup Tool ： NMDPコードからアリル要素を調べる方法

Locus:
A

B

C

DRB1

DRB3

DRB4

DRB5

DQA1

DQB1

DPA1

DPB1

None

Enter a list of alleles and/or allele codes:
15BNUF

クエリ送信

リセット

Allele Code:B*15BNUF -> B*1501/1501N/1504/1505/1507/1508/1512/1514/1515/1519/1520/1523/1524/1525/1532/1533/1534/1537/1550/1556/1557/1570/1575/1578/1579N/1581/1582/1585/1592/1594N/1596
BNUF -> 1501/1501N/1504/1505/1507/1508/1512/1514/1515/1519/1520/1523/1524/1525/1532/1533/1534/1537/1550/1556/1557/1570/1575/1578/1579N/1581/1582/1585/1592/1594N/1596

ACTIVATED for use at:
B*15BNUF

7

6. その他 ドナー検索に関する参考情報

6-1.個別のドナープール状況
希望するドナーが検索されない場合などには、移植調整部までお問い合わせください。検索されたドナー以外にどんなドナーがいるかご案内できます。
例えばこんなことをご案内できます。
例１ 血清フルマッチドナーが 100 人もいるのに、確認検査を実施してみるとどのドナーもアリルが 2 つ以上異なる。
時間と費用ばかりかかっている。
↓
アリルが判明しているドナーの中に、１アリルミスマッチドナーがいるか
例２ 検索されるドナーはいずれもアリルまで判明しているが、どのドナーも患者と不適合。
↓
仮に、血清１抗原不適合検索を行った場合、6 分の 5 アリルマッチドナーがいるか
例３ 患者さんが希なアリルを持つため、適合ドナーがなかなかみつからない↓
希なアリルを適合させることを諦めた場合、他の 5 アリルがマッチしているドナーがいるか
例４ 例えば B 座がホモの患者さん、フルマッチドナーがいない↓
B 座がヘテロで、他の 5 アリルがマッチしているドナーがいるか※お伝えするドナー状況は、あくまでもその時点での情報であり、検索の都度変わる可能性があることをご了承ください。

HLA 相談窓口
当財団では、専門家による「HLA 相談窓口」を設置し、主治医からの HLA に関する問い合わせを受付けています。HLA に関するご質問をお寄せください。回答には約 1 週間を要します。
URL ： http://www.jmdp.or.jp/pt/coordinat/HLA.html
・ 依頼は医師からのみ受け付けています。
・ コンサルティングの結果はあくまでも参考意見であることをご理解いただき、最終的には担当医師がご判断ください。
お問い合わせ先：移植調整部 TEL03-5280-4771／FAX03-5280-3856

8

7. HLA適合度をみる場合の判断例
7-1. 珍しいアリルを持つ場合の判断例① 患者が非常に珍しいアリルを持つ場合は、そのアリルと一致するドナーがみつかる可能性は非常に低いので、アリル型適合のドナー検索は困難と認識して、他の選択肢を考慮する。
② 逆にドナーが非常に珍しいアリルを持つ場合は、そのドナーは避けるか選ばないようにすることで、適合性を高めることができる。
③ P.10〜12「SBT法による確定アリルと蛍光ビーズ法による高頻度アリルの比較表（以下比較表）」に、 高頻度アリ
ルでは同定できない確定アリルとその頻度が示されている（緑色）が、この高頻度アリルが確定アリルと異なる可能性はきわめて低いが存在する。なお、この比較表で緑色で表示されている確定アリルと高頻度アリルの不一致の組合せは、あくまでも今回検討対象となった１７，５５２例のサンプルにおけるもので、その他のアリルにおいてもそれぞれの頻度にしたがって両者の不一致はあり得るものである。したがって、緑色の表示がない場合でも両者の不一致がないことを保証するものではない。
④ ドナーの「SBT法によるHLAオプション検査」は、「特殊なアリル型（Nullアリル*を含む）をもつドナーを避けられる」意味がある。
＊Nullアリル
非発現型のアリル。DNA検査法ではアリルとして認められ表記もされるが、血清型は表記されない。

7-2. 個別の例（A座を例にして）① 患者が0215Nを持つ場合、その遺伝子があってもA2抗原は患者に「表現」されないため、GVHD方向の不適合にならないので臨床的には無視してよい。ただし、選ばれたドナーがA2抗原を表現しているので、HVG方向の不適合になる。
② 逆に、ドナーが0215Nを持つ場合、患者のA2分子はGVHD方向のミスマッチ標的になり、そのドナーを選択する
ことを避けなければならない。
③ 患者がA*2624を持つ場合は、A*2624をもつドナーの検索はほぼできない。
④ A2 アリル型は合わせることを原則にすべきである。GVHDの発症率と重症化傾向が高く、予後不良因子となり得る。
⑤ A26アリル型は合わせることを原則とすべきである。ドナーがまれなA26アリル（A*2605,*2606,*2624）であることがわかれば、それ以外の（患者さんに適合する）ドナーを選ぶことを推奨する。患者さんがまれなA26アリル型である
ときは、アリル型適合ドナーの選択をあきらめ、次善のドナーを選択する。
⑥ A24については、ドナーがまれなアリル型を持っていて、患者（多くはA*2402)に不適合のときはそのドナーを除外して選択することでよいことが多い。患者にまれなA24 アリル型があったときは、その適合を図ることで、時間とコストをかける必要はない。
⑦ まれなA*1121N（Null allele）がドナーとして選択されないように気をつける。

参考：HLAアリルの表記法
HLA ＝ ヒトMHC領域にありHLA遺伝子として同定されている遺伝子の総称
HLA-DRB ＝ HLA 遺 伝 子 領 域 内 の 座 位 の 名 称 、 DR 領 域 に は 他 に 、 DRB1 、 DRB2 （ 偽 遺 伝 子 ） 、 DRB3
（DRB1*11,*12,*13, *14などに連鎖して存在）、DRB4（DRB1*04,*07,*09に連鎖して存在）、DRB5（DRB1 *15, *16などに連鎖して存在）などがあり、それらの総称
HLA-DRB1 ＝ DRB遺伝子のうち、最初に同定された遺伝子座位の名称
HLA-DRB1*13 ＝ アリルの総称。DR13抗原を産生するアリルの総称。俗称：2桁アリル名
HLA-DRB1*1301 ＝ 通常のアリル名。俗称：4桁アリル名
HLA-DRB1*1301N ＝ Null（ナル）アリル。遺伝子は存在するが、完全な分子としてのHLA抗原が表現されない（途中に stop codonが入っている）。
HLA-DRB1*130102 ＝ *1301アリルの一種であるが、塩基に「同義置換」がある。アミノ酸変異を伴わないので、免疫学的（臨床的）にはDRB1*1301と同じに扱うことでよい。俗称：6桁アリル名
HLA-DRB1*13010102 ＝ *1301アリルの一種であるが、非翻訳領域に塩基置換がある。免疫学的（臨床的）には
DRB1*1301と同じに扱うことでよい。俗称：8桁アリル名
HLA-DRB1*13010101N ＝ DR13 Null アリルの一種であるが、非翻訳領域に塩基置換がある

9

8. SBT 法による確定アリルと蛍光ビーズ法による高頻度アリルの比較表
8-1. A ローカス
抗原
A1

N=
67

遺伝子
頻度
0.38%

蛍光ビーズ法
高頻度アリル
0101

SBT 法
確定アリル
0101

N'=
14

抗原型内
頻度
100.00%A2

4,274

24.35%

0201
0201
0203
0205
0206
0207
0207
0210
0211
0218
0228
0242

0201
0275
0203
0205
0206
0207
0215N
0210
0211
0218
0228
0242

1,818
1
4
1
1,548
700
3
51
1
10
5
1

43.88%
0.02%
0.10%
0.02%
37.36%
16.90%
0.07%
1.23%
0.02%
0.24%
0.12%
0.02%

A3

42

0.24%

0301

0301

14

100.00%

A11

1,445

8.23%

1101
1101
1102

1101
1121N
1102

545
1
9

98.20%
0.18%
1.62%

A24

6,971

39.72%

2402
2402
2402
2408
2420

2402
2425
2449
2408
2420

2,473
1
1
2
55

97.67%
0.04%
0.04%
0.08%
2.17%

A26

2,225

12.68%

2601
2601
2602
2603
2605
2606

2601
2624
2602
2603
2605
2606

1,391
1
350
384
14
1

64.97%
0.05%
16.35%
17.94%
0.65%
0.05%

A30

31

0.18%

3001

3001

9

100.00%

A31

1,320

7.52%

3101
3101

3101
3111

509
1

99.80%
0.20%

A32

1

0.01%

A33

1,176

6.70%

3303

3303

410

100.00%

合計

17,552100.00%

10,328＊exon4 の多型は下線で示した。
蛍光ビーズ法では exon2 および 3 を、SBT 法では exon2、3 および 4 について検査を行っていることから、
exon4 のみに塩基置換を伴うアリルに関しては蛍光ビーズ法（高頻度アリル）と SBT 法（確定アリル）とで異なる結果となる。
＊蛍光ビーズ法と SBT 法とで異なるアリルを緑色で示した。
＊Ｎの合計 17,552 は、2003/10/27 以降に採血しＳＢＴ法ＨＬＡ確認検査を実施した、患者・ドナーの合計 8,776 人のＡローカス 2 抗原（17,552 件）を指す。

10

8-2. B ローカス
抗原
B7

N=
1,069

遺伝子
頻度
6.09%

蛍光ビーズ法
高頻度アリル
0702

SBT 法
確定アリル
0702

N'=
351

抗原型内
頻度
100.00%

B13

157

0.89%

1301
1302

1301
1302

25
5

83.33%
16.67%

B27

28

0.16%

2704
2705

2704
2705

8
3

72.73%
27.27%

B35

1,526

8.69%

3501
3503
3552

3501
3503
3552

408
1
1

99.51%
0.24%
0.24%

B37

78

0.44%

3701

3701

23

100.00%

B38

22

0.13%

3802

3802

10

100.00%

B39

655

3.73%

3901
3902
3904

3901
3902
3904

556
42
41

87.01%
6.57%
6.42%

B44

1,110

6.32%

4402
4403

4402
4403

7
283

2.41%
97.59%

B46

928

5.29%

4601

4601

281

100.00%

B48

399

2.27%

4801

4801

96

100.00%

B50

1

0.01%

B51

1,665

9.49%

5101
5102

5101
5102

421
5

98.83%
1.17%

B52

2,176

12.40%

5201

5201

597

100.00%

B54

1,333

7.59%

5401

5401

332

100.00%

B55

380

2.16%

5502
5504

5502
5504

100
3

97.09%
2.91%

B56

136

0.77%

5601
5603
5604

5601
5603
5604

28
9
1

73.68%
23.68%
2.63%

B57

2

0.01%

B58

77

0.44%

5801

5801

15

100.00%

B59

314

1.79%

5901

5901

81

100.00%

B60

858

4.89%

4001
4001
4054

4001
4055
4054

273
1
1

99.27%
0.36%
0.36%

B61

2,583

14.72%

4002
4002
4002V8
4003
4004
4006
4050

4002
4056
4002V8
4003
4004
4006
4050

1,465
1
1
73
1
926
1

59.36%
0.04%
0.04%
2.96%
0.04%
37.52%
0.04%

B62

1,540

8.77%

1501
1501
1507
1515
1527
1528
1592

1501
1501V5
1507
1515
1527
1528
1592

1,341
9
116
1
20
7
1

89.70%
0.60%
7.76%
0.07%
1.34%
0.47%
0.07%

B67

144

0.82%

6701

6701

36

100.00%

B71

237

1.35%

1518

1518

67

100.00%

B72

1

0.01%

1546

1546

1

100.00%

B75

132

0.75%

1502
1511

1502
1511

4
127

3.05%
96.95%

B77

1

0.01%

合計

17,552100.00%8,206＊exon4 の多型は下線で示した。
蛍光ビーズ法では exon2 および 3 を、SBT 法では exon2、3 および 4 について検査を行っていることから、exon4 のみに塩基置換を伴うアリルに関しては蛍光ビーズ法（高頻度アリル）と SBT 法（確定アリル）とで異なる結果となる。
＊蛍光ビーズ法と SBT 法とで異なるアリルを緑色で示した。
＊Ｎの合計 17,552 は、2003/10/27 以降に採血しＳＢＴ法ＨＬＡ確認検査を実施した、患者・ドナーの合計 8,776 人の B ローカス 2 抗原（17,552 件）を指す。

11

8-3. DR ローカス
抗原
DR1

N=
1,053

遺伝子
頻度
6.00%

蛍光ビーズ法
高頻度アリル
0101

SBT 法
確定アリル
0101

N'=
1,053

抗原型内
頻度
100.00%

DR4

4,420

25.18%

0401
0403
0403
0404
0405
0406
0407
0410
0413

0401
0403
0452
0404
0405
0406
0407
0410
0413

207
582
1
53
2,447
632
84
413
1

4.68%
13.17%
0.02%
1.20%
55.36%
14.30%
1.90%
9.34%
0.02%

DR7

48

0.27%

0701

0701

48

100.00%

DR8

2,162

12.32%

0802
0803
0809
0823

0802
0803
0809
0823

650
1,505
6
1

30.06%
69.61%
0.28%
0.05%

DR9

2,700

15.38%

0901

0901

2,700

100.00%

DR10

72

0.41%

1001

1001

72

100.00%

DR11

389

2.22%

1101
1123

1101
1123

386
3

99.23%
0.77%

DR12

660

3.76%

1201
1202
1205

1201
1202
1205

474
185
1

71.82%
28.03%
0.15%

DR13

1,096

6.24%

1301
1302
1307

1301
1302
1307

51
1,043
2

4.65%
95.16%
0.18%

DR14

1,548

8.82%

1401
1402
1403
1405
1405
1406
1407
1412
1429

1401
1402
1403
1405
1445
1406
1407
1412
1429

621
4
307
362
1
235
12
5
1

40.12%
0.26%
19.83%
23.39%
0.06%
15.18%
0.78%
0.32%
0.06%

DR15

3,299

18.80%

1501
1502
1506
1515

1501
1502
1506
1515

1,232
2,065
1
1

37.34%
62.63%
0.03%
0.03%

DR16

99

0.56%

1602

1602

99

100.00%

DR17

6

0.03%

0301

0301

6

100.00%

合計

17,552100.00%17,552＊蛍光ビーズ法と SBT 法と異なるアリルを緑色で示した
蛍光ビーズ法では exon2 および 3 を、SBT 法では exon2、3 および 4 について検査を行っていることから、
exon4 のみに塩基置換を伴うアリルに関しては蛍光ビーズ法（高頻度アリル）と SBT 法（確定アリル）とで異なる結果となる。
＊Ｎの合計 17,552 は、2003/10/27 以降に採血しＳＢＴ法ＨＬＡ確認検査を実施した、患者・ドナーの合計 8,776 人の DR ローカス 2 抗原（17,552 件）を指す。

12

9. 解析資料集＜目次＞

１．重症急性 GVHD ハイリスクな HLA 型の組み合わせについて

P.14

2. 非血縁者間骨髄移植における HLA-C 適合度の解析

P.16

3. HLA 適合度に基づいた治療成績の分析

P.18

4.HLA ALLELE MISMATCH COMBINATIONS AND AMINO ACID SUBSTITUTIONSRESPONSIBLE
FOR
ACUTE
GRAFT-VERSUS-HOSTDISEASEIN
HEMATOPOIETIC STEM CELL TRANSPLANTATION

P.20

5. T 細胞非除去非血縁者間骨髄移植を受けた白血病患者における HLA 型と KIR リガ
ンド適合度の臨床成績への影響について（5.の日本語版抄録）

P.27

6. Effects of HLA Allele and Killer Immunoglobulin-Like Receptor Ligand Matching on
Clinical Outcome in Leukemia Patients Undergoing Transplantation WithT-cell-Replete Marrow From an Unrelated Donor

P.28

7. ミスマッチ症例における急性 GVHD Grade3-4 発症率

P.42

13

重症急性 GVHD ハイリスクな HLA 型の組み合わせについて
2007 年 3 月

骨髄移植推進財団

HLA 委員会

日本骨髄バンクを介した非血縁者間骨髄移植の成績とドナー・患者 HLA 型との解析から、
重症急性 GVHD が起こりやすい特定の HLA 型の組み合わせが次第に明らかになってきました。骨髄移植推進財団 HLA 委員会では、ドナー選択の上で、これらの重症急性 GVHDが起こりやすい HLA 型の組み合わせの情報が有用であると判断しましたので、移植病院の先生方にお知らせすることとしました。

[表の説明]
5,200 例の HLA-A,B,DR 血清型適合移植例につき、HLA-A,B,C,DRB1,DQB1,DPB1 のアリル型を後方視的に同定し、各 HLA 座の適合度と臨床因子を考慮に入れ、Cox hazard
model による多変量解析を実施しました。それぞれの HLA 型不適合の組み合わせ別に、急性 GVHD の発症危険率を同一 HLA 座の適合症例との相対危険率（Hazard Ratio: HR）として計算しました。これらのうち、有意水準を P <0.005 としても GVHD 発症の相対危険率が高いと判断された HLA 型不適合の組み合わせを抽出し、さらに、ブートストラップ法
でも有意差が確認されたものを、重症 GVHD ハイリスクな組み合わせと定義しました。合わせて、これらの組み合わせにつき、移植後死亡の相対危険率も示しました。

14

ドナー選択時の参考資料とする場合には、以下の点に留意してご利用ください。
１．表で示した組み合わせは、重症 GVHD の発症リスクの高い組み合わせであり、生存への影響については有意でないものがあること。
（生存も有意な組み合わせには●印を記載しました。）
２．これら以外にも、重症 GVHD の発症頻度が高い組み合わせが存在する可能性があること（組み合わせによっては、症例数が少ないため有意にならなかった可能性もあります）。したがって、この組み合わせ以外の HLA 型不適合が、GVHD が起こりに
くい組み合わせとは断定できないこと。
３．この表の組み合わせは、様々な GVHD 予防法（Ｔ細胞除去法を除く）や疾患を含んだ多変量解析の結果であること。
４．論文化前のデータであること。
５．2006 年 2 月資料（HLA 適合度に基づいた治療成績の分析、ＮＫ細胞受容体リガン
ド適合度の同定）資料添付、ならびに、最近論文化された論文：Morishima Y, Yabe
T, Matsuo K, Kashiwase K, Inoko H, Saji H, Yamamoto K, Maruya E, Akatsuka Y,
Onizuka M, Sakamaki H, Sao H, Ogawa S, Kato S, Juji T, Sasazuki T, Kodera Y;
Japan

Marrow

Donor

Program:

Effectsof

HLA

AlleleandKillerImmunoglobulin-Like Receptor Ligand Matching on Clinical Outcome in
Leukemia Patients Undergoing Transplantation With T-cell-Replete Marrow
From an Unrelated Donor.

Biol Blood Marrow Transplant. 2007 Mar;13(3):315-28.）も参照してください。

【HLA 相談窓口のご案内】
ドナー・患者の HLA ならびに HLA 適合度に基づくドナー選択に関して、HLA 委員会
委員を中心にして HLA 相談窓口を設けています。何なりとご相談ください。
問い合わせ先：骨髄移植推進財団

15

移植調整部（電話 03-5280-4771）

非血縁者間骨髄移植における HLA-C 適合度の解析 : update2007 年 10 月 12 日

骨髄移植推進財団 HLA 委員会

HLA-A、B, DR の血清型が適合した JMDP5210 症例につき解析した。T 細胞除去 GVHD 予防法症例で、解析は多変量解析（Cox regression model）を用い、変数として[症例]に示した臨床的な因子と他座の適合度を用いた。
[症例] 急性リンパ性白血病 1301 例 急性骨髄性白血病 1405 例、慢性骨髄性白血病 887 例 骨髄異形性症候群 597
ATG 未使用 4810 例
例 悪性リンパ腫 453 例 再生不良性貧血 302 例 GVHD 予防法：ATG 使用 400 例
シクロスポリン使用 2733 例 タクロリムス使用 2437 例 移植前治療：全身放射線照射 4021 例 非照射 1189 例
全例骨髄破壊的全治療実施
HLA 座不適合の割合（GVH 方向）
HLA-A
13.4%
HLA-B
6.4%
HLA-C
29.2%
HLA-DRB1 19.6%
HLA-DQB1 22.5%
HLA-DPB1 65.7%．

16

17

HLA 適合度に基づいた治療成績の分析
2006 年 2 月 25 日(財)骨髄移植推進財団

HLA 委員会

HLA-A, B, C, DRB1 の DNA 型が判明した場合の治療成績について、適合度別の 3 年生存率、6年生存率、重症 GVHD 発症率を示した。HLA-C の適合度が臨床成績に影響している。JMDP を介して実施された最初から 3000 症例の中で HLA-A, B, DR の血清型が適合し DNA 型レトロスペクティブに解析された全 2500 症例を対象とした。異なった疾患・病期・GVHD 予防法が含まれることと、群によっては症例数が少ないことに留意されたい。また、この分析結果は、今後のドナー選択の際の参考資料となるものと考える。
○ HLA 遺伝子型適合 × HLA 遺伝子型 1 型不適合

P は全適合症例との比較。

ｎ

3 年生存

6 年生存

P

A-GVHD(grade3,4)

P

○

DR
B1
○

1128

58%

52%

-

13%

-

○

○

×

219

55

53

0.745

14

0.536

○

○

×

○

371

54

45

0.052

20

0.001

4

○

○

×

×

172

49

48

0.011

28

<0.0001

5a

×

○

○

○

155

42

36

<0.0001

22

0.001

5b

○

×

○

○

22

34

-

0.013

28

<0.0001

6a

○

×

×

○

84

37

37

<0.000131<0.0001

6b

×

○

×

○

100

31

30

<0.000131<0.0001

6c

×

○

○

×

30

35

28

0.003

15

0.697

6d

○

×

○

×

19

26

20

0.001

28

0.046

6e

×

×

○

○

7

ne

ne

7a

○

×

×

×

28

42

18

0.009

38

0.0002

7b

×

○

×

×

47

31

31

<0.000135<0.0001

7c

×

×

○

×

6

ne

ne

7d

×

×

×

○

34

30

27

0.000441<0.0001

8

×

×

×

×

19

24

16

<0.0001

28

0.029

A

B

C

1

○

○

2

○

3

ne

ne

ne ：症例数が 9 例以下のため解析せず。a, b, c, d, e は順位ではない。

HLA-C 不適合移植（3. 4.）における NK 細胞受容体(KIR:NKG2L) ligand 適合の成績
KIR 不適合：GVHD 方向のデータ

A

B

C

DR
B1

KIR

ｎ

3 年生存

6 年生存

P

A-GVHD(grade3,4)P

HLA-C 単独不適合
3a

○

○

×

○

○

324

56%

47%

-

18%

-

3b

○

○

×

○

×

52

40

20

0.016

34

0.008

HLA-C + DRB1 不適合
4a

○

○

×

×

○

147

53

53

-

25

-

4b

○

○

×

×

×

29

34

28

0.012

41

0.085

18

NK 細胞受容体（KIR２DL）と移植との解説
NK 細胞受容体の一つである KIR２DL の KIR２DL２と KIR２DL３は HLA−C のアミノ酸
配列 Ser77,Asp80（Ｃｗ３group エピトープ）と結合して NK 細胞の活性化を抑制している。
KIR２DL1 は HLA-C の配列 Asp77, Lys80（Ｃｗ４group エピトープ）と結合して NK 細胞の活性化を抑制している。 HLA-C 抗原は下表に示すようにＣｗ３group かＣｗ４group のど
ちらかのエピトープを有する。
造血細胞移植ではドナー由来の造血細胞に置き換わるため、HLA-C 不適合移植においては、
以下に示すように患者（あるいはドナー）の KIR２DL と結合する HLA-C のエピトープが存在しない場合があり、このため患者（あるいはドナー）の KIR 陽性細胞が活性化され、GVHD（あるいは拒絶）が生じる可能性がある。KIR の GVHD 方向（拒絶方向）の不適合は通常のリンパ球による HLA 不適合とは逆方向になる。
HLA-C 型から KIR２DL リガンド適合度を見出す手順。
下表（A）を用いドナーと患者の HLA-C 型から HLA-C のエピトープ（Cw3 group か Cw4group か）を決め、下表（B）に当てはめ、ligand の適合度を見出す。
表A
HLA−C エピトープ

HLA 型
Cw 4 group
血清型
Cｗ2, Cw4, Cw5, Cw6(Asp77, Lys80)
Cw*0401, Cw*0501, Cw*0602, Cw*1502
遺伝子型
Cw 3 group
血清型
Cｗ１, Cw3, Cw7, Cw8, Cw10
(Ser77, Asp80)
Cw*0102, Cw*0302, Cw*0303, Cw*0304, Cw*0702,
遺伝子型
Cw*0704,Cw*0801, Cw*0803, Cw*1202 Cw*1402
Cw*1403
参考：JMDP での頻度 Cw4 group 7.3％ Cw3 group 92.7％
表B
適合度

患者

ドナー

JMDP での頻度

GVHD 方向の不適合

Cw3 Cw3
Cw4 Cw4

Cw3 Cw4
Cw3 Cw4

4.6％

拒絶方向の不適合

Cw3 Cw4
Cw3 Cw4

Cw3 Cw3
Cw4 Cw4

5.8％

両方向の不適合.

Cw3 Cw3
Cw4 Cw4

Cw4 Cw4
Cw3 Cw3

0.5％

適合

Cw3 Cw4
Cw3 Cw3
Cw4 Cw4

Cw3 Cw4
Cw3 Cw3
Cw4 Cw4

89.2％

Cw3 : Cw3 group

Cw4 : Cw4 group

19

Plenary paper

High-risk HLA allele mismatch combinations responsible for severe acutegraft-versus-host disease and implication for its molecular mechanism
Takakazu Kawase,1 Yasuo Morishima,2 Keitaro Matsuo,3 Koichi Kashiwase,4 Hidetoshi Inoko,5 Hiroh Saji,6 Shunichi Kato,7Takeo Juji,8 Yoshihisa Kodera,9 and Takehiko Sasazuki,10 for The Japan Marrow Donor Program
1Division of Immunology, Aichi Cancer Center, Nagoya; 2Department of Hematology and Cell Therapy, Aichi Cancer Center, Nagoya; 3Division of Epidemiology
and Prevention, Aichi Cancer Center, Nagoya; 4Japanese Red Cross Tokyo Metropolitan Blood Center, Tokyo; 5Division of Molecular Science, Tokai University
School of Medicine, Isehara; 6Human Leukocyte Antigen (HLA) Laboratory, Nonprofit Organization (NPO), Kyoto; 7Department of Cell Transplantation andRegenerative Medicine, Tokai University School of Medicine, Isehara; 8Japanese Red Cross Central Blood Institute, Tokyo; 9Japanese Red Cross Nagoya First
Hospital, Nagoya; 10International Medical Center of Japan, Tokyo, Japan

In allogenic hematopoietic stem-celltransplantation, an effect of HLA locus
mismatch in allele level on clinical outcome has been clarified. However, theeffect of each HLA allele mismatch combination is little known, and its molecular mechanism to induce acute graftversus-host disease (aGVHD) remains
to be elucidated. A total of 5210 donorpatient pairs who underwent transplantation through Japan Marrow Donor Program were analyzed. All HLA-A, -B, -C,-DRB1, -DQB1, and -DPB1 alleles wereretrospectively typed in all pairs. The

impacts of the HLA allele mismatch combinations and amino acid substitution
positions in 6 HLA loci on severe aGVHD
were analyzed. A total of 15 significant
high-risk HLA allele mismatch combinations and 1 HLA-DRB1-DQB1 linked
mismatch combinations (high-risk mismatch) for severe aGVHD were identified, and the number of high-risk mismatches was highly associated with theoccurrence of severe aGVHD regardlessof the presence of mismatch combinations other than high-risk mismatch.
Furthermore, 6 specific amino acid sub-stitution positions in HLA class I wereidentified as those responsible for severe aGVHD. These findings provide
evidence to elucidate the mechanism of
aGVHD on the basis of HLA molecule.
Furthermore, the identification of highrisk mismatch, that is, nonpermissivemismatch, would be beneficial for theselection of a suitable donor. (Blood.
2007;110:2235-2241)© 2007 by The American Society of Hematology

Introduction
Allogenic hematopoietic stem-cell transplantation (HSCT) froman HLA-matched unrelated (UR) donor has been established asa treatment for hematologic malignancies, when an HLAidentical sibling donor is unavailable.1,2 When a matchedunrelated donor was not found in the donor registry, a partially
HLA-matched unrelated donor was one of the candidates foralternative donor. But the higher risk of immunologic events,
especially graft-versus-host disease (GVHD), was an important
drawback. Extensive recent research has accumulated evidenceof the role of each HLA locus mismatch on clinical outcome for
UR-HSCT,3-9 which has made it easy to search and select apartially matched donor. To further expand options for donor
selection, our next challenge is to identify permissive andnonpermissive mismatch combinations of each HLA allele.
Although there were some divisional trials with small populations,10,11 a large-scale cohort is essential for comprehensive
analysis to identify nonpermissive mismatch combinations thatare significant risk factors for severe acute graft-versus-hostdisease (aGVHD).
In this study, we identified nonpermissive HLA mismatch allele
combinations of all major 6 HLA loci, and their responsible
positions of amino acid substitution for aGVHD.

Patients, materials, and methods
Patients
A total of 5210 donor-patient pairs who underwent transplantation throughthe Japan Marrow Donor Program (JMDP) with T-cell–replete marrowfrom a serologically HLA-A, -B, and -DR antigen-matched donor between
January 1993 and January 2006 were analyzed in this cohort study. Patients
who received a transplant of harvested marrow outside Japan (n ⫽ 51) or
were unavailable for blood sample (n ⫽ 428) were not eligible for thisstudy of a total of 5689 consecutively registered patients.
Patient characteristics are shown in Table S1, available on the Bloodwebsite (see the Supplemental Materials link at the top of the online article).
The final clinical survey of these patients was completed by June 1, 2006.
Informed consent was obtained from patients and donors in accordancewith the Declaration of Helsinki, and approval of the study was obtained
from the Institutional Review Board of Aichi Cancer Center and JMDP.
HLA typing of patients and donors
Alleles at the HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1 loci wereidentified by the methods described previously.4,5 Six HLA locus alleles
were typed in all 5210 pairs. HLA genotypes of HLA-A, -B, -C, -DQB1,
and -DPB1 allele of patient and donor were reconfirmed by the Luminex
microbead method (Luminex 100 System; Luminex, Austin, TX). For
convenience, we showed the frequency of HLA alleles that existed with

Submitted February 6, 2007; accepted June 4, 2007. Prepublished online as
Blood First Edition paper, June 6, 2007; DOI 10.1182/blood-200702-072405.

The publication costs of this article were defrayed in part by page charge
payment. Therefore, and solely to indicate this fact, this article is hereby
marked ‘‘advertisement’’ in accordance with 18 USC section 1734.

The online version of this article contains a data supplement.

© 2007 by The American Society of Hematology

BLOOD, 1 OCTOBER 2007 䡠 VOLUME 110, NUMBER 7

2235

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BLOOD, 1 OCTOBER 2007 䡠 VOLUME 110, NUMBER 7

KAWASE et al

more than a 5% allele frequency in the current Japanese data set and lessthan a 1% allele frequency in white populations12 in Table S2.
Matching of HLA allele between patient and donor
For the analysis of aGVHD, HLA allele mismatch among the donorrecipient pair was scored when the recipient’s alleles were not shared by thedonor (GVH vector). We also used GVH vectors for the analysis of overall
survival (OS) to indicate OS of aGVHD high-risk or low-risk group.
Evaluation of acute GVHD
Occurrences of aGVHD were graded with grade 0, I, II, III, and IV
according to established criteria.13 Grades III and IV were defined assevere aGVHD.
Definitions of amino acid substitution
Amino acid sequences of HLA-A, -B, -C, -DR, -DQ, and -DP molecules
were obtained from IMGT/HLA sequence database.14 For example, Tyr9APhe9A indicated amino acid substitutions of position 9 in HLA-A moleculeat which the donor had tyrosine and the patient phenylalanine. Substituted
amino acids in HLA class I were summarized in Tables S3-S5.
Definition of nonpermissive HLA combinations
We defined the nonpermissive HLA allele combination as a significant risk
factor for severe aGVHD, because severe aGVHD was a solid marker foralloreactivity in HSCT and was the main contributor to transplantationrelated mortality.15,16
Definition of hydropathy scale
The hydropathy scale proposed by Kyte and Doolittle17 evaluates thehydrophilicity and hydrophobicity of 20 amino acids to estimate theprotein structure. Hydrophobic amino acid has a plus value andhydrophilic amino acid a minus value, and their absolute value indicatesthe grade of each property.

We analyzed the impact of each amino acid substitution on each position
separately. Multivariable Cox models including positions and types ofamino acid substitution, mismatch status in other loci (match, 1 locus
mismatch, and 2 locus mismatches as ordinal variable), and confounders
described in “Statistical analysis” were constructed.
We applied a P value of less than .005 as statistically significant toeliminate false-positive associations. All the analyses were conducted by
STATA version 9.2 (Stata, College Station, TX).
Validation of statistical analysis
We validated the statistical analysis using 2 methods, traditional trainingand-test method and bootstrap resampling method, in HLA-A analysis toconfirm the usability of bootstrap resampling. In the traditional training-andtest method, donor-recipient pairs were divided at random in 2 equallyscaled groups, group A and group B. When consistent results were obtainedin both analyses, we considered the results as validated. In the bootstrap
resampling method,22 we estimated the measure of association with theresampled data repeatedly drawn from the original data. Although around
100 to 200 bootstrapped samplings are generally sufficient,23 we explored
500, 1000, 5000, 10 000, and 50 000 bootstrappings in analysis of HLA-A
mismatch combinations. We confirmed that an analysis using more than
5000 bootstrappings made the results stable. Because there was highconcordance between these 2 methods (Table S6), we adopted bootstrap
resampling using 10 000 bootstrap samples for all analyses in this paper as
the method for validation. This is because traditional training-and-test
methods do not work efficiently when small subgroups are considered as inthis paper. Only when the results of base analysis and validating analysis
using bootstrap resampling were significant concurrently were theresults of the analysis judged to be statistically significant. When the
result of base analysis was significant but the result of validating
analysis using bootstrap resampling was not, we indicated this by adding
an asterisk next to the P value of the base analysis.

Results

Statistical analysis

Impact of HLA allele mismatch combinations on severe aGVHD

Cumulative incidences of aGVHD were assessed by the method described
elsewhere to eliminate the effect of competing risk.18,19 The competing
event regarding aGVHD was defined as death without aGVHD. A log-rank
test was applied to assess the impact by the factor of interest. Multivariable
Cox regression analyses20 were conducted to evaluate the impact of HLA
allele mismatch combination, and the positions and types of amino acidsubstitution (for example, alanine, arginine, asparagines) of HLA molecules.
The HLA mismatch combination was evaluated for each locus separately, and the HLA match and HLA one-locus mismatch in every locus
were analyzed. For example, A0206-A0201 mismatch combination meantthat the donor has HLA-A*0206, recipient has HLA-A*0201, and another
HLA-A allele of each donor and recipient was identical. This mismatch wascompared with the HLA-A allele match. The mismatch combination ofwhich the number of pairs was less than 10 was lumped together as “othermismatch.” This is because, according to the computer simulation by
Peduzzi et al,21 it is generally accepted that regression analysis for avariable having fewer than 10 events might give an unreliable estimation.
The model was constructed with mismatch combinations, mismatch status
in other loci (match, 1 locus mismatch, and 2 locus mismatches as ordinalvariable), and potential confounders. Confounders considered were sex(donor-recipient pairs), patient age (linear), donor age (linear), type of
disease, risk of leukemia relapse (standard, high, and diseases other thanleukemia), GVHD prophylaxis (cyclosporine [CSP] vs FK 506 [FK]), ATG(ATG vs no ATG), and preconditioning (total body irradiation [TBI] vsnon-TBI). We used these confounders in all analyses in this paper to keep
results comparable.
The impact of positions and types of amino acid substitution in HLA
molecules was evaluated in pairs with HLA one-locus mismatch in HLA-A,-B, -C, -DRB1, -DQB1, and -DPB1 separately. The amino acid positions weanalyzed were all those at which amino acid was substituted in each locus.

Hazard ratios (HRs) of HLA allele mismatch combinations in
HLA-A and -C on severe aGVHD are shown in Table 1 (HLA-B,-DR, -DQ, and -DP are available in Table S7).
In HLA-A locus mismatch combinations, A*0206-A*0201(HR: 1.78; CI, 1.32-2.41), A*0206-A*0207 (HR: 3.45; CI: 2.095.70), A*2602-A*2601 (HR: 3.35; CI: 1.89-5.91), and A*2603A*2601 (HR: 2.17; CI: 1.29-3.64), were significant risk factors forsevere aGVHD.
In HLA-C locus mismatch combinations, 7 combinations
were significant risk factors for severe aGVHD; those were as
follows: Cw*0401-Cw*0303 (HR: 2.81; CI: 1.72-4.60),
Cw*0801-Cw*0303 (HR: 2.32; CI: 1.58-3.40), Cw*0303Cw*1502 (HR: 3.22; CI: 1.75-5.89), Cw*0304-Cw*0801 (HR:2.34; CI: 1.55-3.52), Cw*1402-Cw*0304 (HR: 3.66; CI: 2.006.68), Cw*1502-Cw*0,304 (HR: 3.77; CI: 2.20-6.47), andCw*1502-Cw*1402 (HR: 4.97; CI: 3.41-7.25). To summarize,
high-risk HLA allele mismatch combinations for severe aGVHD,
that is, nonpermissive mismatch combinations, of all major 6
HLA loci were listed in Table 2. A total of 15 nonpermissive
HLA allele mismatch combinations (4 in HLA-A, 1 in HLA-B, 7
in HLA-C, 1 in HLA-DRB1, and 2 in HLA-DPB1) and 1
HLA-DRB1-DQB1 linked mismatch combination (Table 2
legend) were identified.
We divided donor-recipient pairs into 4 groups according to thenumber of nonpermissive mismatches: (1) full match (in HLA-A,-B, -C, -DRB1, -DQB1, and -DPB1) group; (2) zero nonpermissivemismatch (with mismatches other than nonpermissive mismatches)BLOOD, 1 OCTOBER 2007 䡠 VOLUME 110, NUMBER 7

HIGH-RISK HLA MISMATCH COMBINATIONS FOR aGVHD

Table 1. Multivariable analysis of impact of mismatch pairs
for sever aGVHD in HLA-A and -C

2237

Table 2. Nonpermissive allele mismatch combinations
for severe aGVHD

Mismatch combination,
donor-patientN

HR (95% CI)

P

Mismatch combination,
donor-patientN

HR (95% CI)

P

A locus match

4510

1

NA

A0206-A0201

131

1.78 (1.32-2.41)⬍ .001

A0201-A0206

138

1.23 (0.87-1.73).223

A0206-A0207

27

3.45 (2.09-5.70)⬍ .001

A0206-A0201

131

1.78 (1.32-2.41)⬍ .001

A2602-A2601

21

3.35 (1.89-5.91)⬍ .001

A0201-A0207

28

0.83 (0.34-2.03).699

A2603-A2601

35

2.17 (1.29-3.64).003

A0207-A0201

20

1.12 (0.42-3.02).809

B1501-B1507

19

3.34 (1.85-5.99)⬍ .001

A0201-A0210

111.57 (0.58-4.23).367

C0303-C1502

25

3.22 (1.75-5.89)⬍ .001

A0206-A0207

27

3.45 (2.09-5.70)⬍ .001

C0304-C0801

69

2.34 (1.55-3.52)⬍ .001

A0207-A0206

220.71 (0.23-2.24).571

C0401-C0303

42

2.81 (1.72-4.60)⬍ .001

A2402-A2420

60

0.64 (0.32-1.30).225

C0801-C0303

80

2.32 (1.58-3.40)⬍ .001

A2420-A2402

30

1.18 (0.56-2.49).66

C1402-C0304

23

3.66 (2.00-6.68)⬍ .001

A2601-A2602

24

0.64 (0.26-1.58).34

C1502-C0304

27

3.77 (2.20-6.47)⬍ .001

A2602-A2601

21

3.35 (1.89-5.91)⬍ .001

C1502-C1402

50

4.97 (3.41-7.25)⬍ .001

A2601-A2603

34

1.37 (0.73-2.57).326

DR0405-DR0403

53

2.13 (1.28-3.53).003

A2603-A2601

35

2.17 (1.29-3.64).003(DR1403-DQ0301)-

A2602-A2603

10

1.23 (0.30-4.98)

.763

19

2.81 (1.44-5.51).002

A2603-A2602

12

1.50 (0.48-4.68).485

DP0301-DP0501

49

2.41 (1.49-3.89)⬍ .001.047

DP0501-DP0901

71

2.03 (1.30-3.16)

.002

97

1.47 (1.00-2.15)

C locus match

A other mismatch

3685

1

NA

C0102-C0303

30

2.83 (1.50-5.32).001*

C0303-C0102

38

1.05 (0.47-2.36).899

C0102-C0304

12

1.85 (0.59-5.81).287

C0304-C0102

19

0.89 (0.28-2.79).854

C0102-C0401

141.87 (0.77-4.55).164

C0102-C0803

24

1.97 (0.87-4.42).099

C0803-C0102

10

1.66 (0.53-5.19).383

C0102-C1402

16

3.86 (1.98-7.51)⬍ .001*

C1402-C0102

130.46 (0.06-3.33).45

C0303-C0304

83

1.08 (0.63-1.85).761

C0304-C0303

62

0.83 (0.41-1.68).614

C0303-C0401

31

1.73 (0.89-3.36).103

C0401-C0303

42

2.81 (1.72-4.60)⬍ .001

C0303-C0702

25

1.16 (0.52-2.62).706

C0702-C0303

18

2.16 (0.96-4.85).062

C0303-C0801

76

1.07 (0.63-1.84).782

C0801-C0303

80

2.32 (1.58-3.40)⬍ .001

C0303-C1502

25

3.22 (1.75-5.89)⬍ .001

C0304-C0401

15

3.02 (1.34-6.79).007

C0401-C0304

12

6.22 (3.07-12.5)⬍ .001*

C0304-C0702

26

2.35 (1.16-4.76).017

C0702-C0304

33

1.22 (0.58-2.59).59

C0304-C0801

69

2.34 (1.55-3.52)⬍ .001

C0801-C0304

47

1.64 (0.98-2.76).057

C0304-C1402

28

3.06 (1.68-5.60)⬍ .001*⬍ .001

C1402-C0304

23

3.66 (2.00-6.68)

C0304-C1502

53

1.82 (1.08-3.05).023

C1502-C0304

27

3.77 (2.20-6.47)⬍ .001

C0801-C0102

10

2.88 (0.92-9.03).068

C0801-C0803

27

1.55 (0.69-3.48).284

C0803-C0801

26

2.04 (1.04-3.99).037

C0801-C1502

36

1.59 (0.79-3.21).19

C1502-C0801

23

2.28 (1.07-4.85).031

C1402-C1502

55

1.67 (1.01-2.77).043

C1502-C1402

50

4.97 (3.41-7.25)⬍ .001C other mismatch

347

1.69 (1.34-2.14)⬍ .001

A0206-A0201 mismatch combination meant that the donor has HLA-A*0206, recipienthas HLA-A*0201 and another HLA-A allele of each donor and recipient was identical. Eachmismatch pair in HLA-A was compared with the HLA-A allele match, and each mismatch
pair in HLA-C was compared with the HLA-C allele match. Confounders considered weresex (donor-recipient pairs), patient age (linear), donor age (linear), type of disease, risk ofleukemia relapse (standard, high and diseases other than leukemia), GVHD prophylaxis,(CSP vs. FK), ATG (ATG vs. no ATG) and preconditioning (TBI vs non-TBI).
HR denotes hazard ratio; CI, confidence interval; NA, not applicable.
*The result of base analysis was significant, but the result of validating analysis
using bootstrap resampling was not. The results of the analysis were thus judged not
to be statistically significant.

(DR1401-DQ0502)

Analysis method is the same as in Table 1. We surveyed specific linked
mismatches between nonpermissive mismatches elucidated. As a result, obvious
specific linked mismatches exist only between DRB1*1403- DRB1*1401 andDQB1*0301- DQB1*0502. Therefore, we could not evaluate which mismatch
combination impacted aGVHD, and we considered this linked mismatch did so.
On the other hand, because other nonpermissive mismatch combinations had no
specific link with the others, we judged other than DRB1*1403- DRB1*1401 andDQB1*0301- DQB1*0502 nonpermissive mismatches solely impacted aGVHD.
(DR1403-DQ0301)-(DR1401-DQ0502) linked mismatch meant that the donor has
HLA-DRB1*1403-HLADQB1*0301 and the recipient has HLA-DRB1*1401HLADQB1*0502.
HR indicates hazard ratio; CI, confidence interval.

group; (3) 1 nonpermissive mismatch (with or without mismatches
other than nonpermissive mismatches) group; and (4) 2 or more
nonpermissive mismatches (with or without mismatches other thannonpermissive mismatches) group, and analyzed for association
with severe aGVHD. This analysis excluded pairs with 2 locus
mismatches in the same locus. Patient characteristics according to
the number of nonpermissive mismatches are shown in Table 3.
The curve of cumulative incidence of severe aGVHD is shown in
Figure 1A. Multivariable analysis revealed that severe aGVHD
occurred with almost equal frequency between the full match groupand zero nonpermissive mismatch group, and was significantly
associated with the number of nonpermissive mismatches (Table4). Relative risk of significant factor for aGVHD and OS is shownin Table S8. In terms of the mortality due to aGVHD according to
the number of nonpermissive mismatches, one nonpermissivemismatch group and 2 or more nonpermissive mismatch groups
showed higher mortality (19.7% and 15.8%, respectively) than fullmatch group and zero nonpermissive mismatch group (8.5% and11.4%, respectively).
Impact of positions and types of amino acid substitutions of
HLA molecules for severe aGVHD

One specific amino acid substitution at position 9 in HLA-A
molecule and 6 specific amino acid substitutions at positions 9, 77,
80, 99, 116, and 156 in HLA-C molecule were significant risk
factors for severe aGVHD: Tyr9A-Phe9A (HR: 1.66; CI: 1.193.32), Tyr9C-Ser9C (HR: 1.66; CI: 1.23-2.25), Asn77C-Ser77C(HR: 1.87; CI: 1.46-2.39), Lys80C-Asn80C (HR: 1.87; CI: 1.462.39), Tyr99C-Phe99C (HR: 1.64; CI: 1.21-2.22), Leu116CSer116C (HR: 3.40; CI: 2.20-5.25), and Arg156C-Leu156C (HR:1.48; CI: 1.15-1.90) (Table 5). The amplitude of hydropathy scales
were 4.1, 0.5, 2.7, 0.4, 4.1, 4.6, and 8.3, respectively. Although all

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KAWASE et al

Table 3. Patient characteristics according to number of nonpermissive mismatches
Total

Full
match

Zero nonpermissivemismatch

One nonpermissivemismatch

4050

712

2670

602

66

30

32

30

29

29

Male/male

1673

312

1096

237

28

Male/female

785

134

518

119

14

Female/male

769

115

524

117

13

Female/female

823

151

532

129

11

ALL

981

162

668

139

12

ANLL

1075

196

698

158

23

CML

703

119

453

115

16

Hereditary disease

85

14

56

15

0

MDS

476

91

304

72

9

Malignant lymnphoma

349

69

229

48

3

Group
Total
Patient age, median y

Two or more nonpermissivemismatches

Sex, donor/patient, no. patients

Disease, no. patients

Multiple myeloma

42

8

29

4

1

Severe aplastic anemia

247

33

175

37

2

Other disease

92

20

58

14

0

Standard risk

1308

249

857

181

21

High risk

1451

228

962

231

30

Diseases other than leukemia

1291

235

851

190

15

Cyclosporin-based

2198

402

1444

319

33

Tacrolimus-based

1852

310

1226

283

33

Risk of leukemia relapse,* no. patients

GVHD prophylaxis, no. patients

ATG, no. patients
ATG

323

48

215

53

7

Non-ATG

3727

664

2455

549

59

Preconditioning, no. patients
TBI regimen

3117

539

2071

449

58

Non-TBI regimen

933

173

599

153

8

ALL indicates acute lymphoblastic leukemia; ANLL, acute non-lymphoblastic leukemia; CML, chronic myeloid leukemia; MDS, myelodysplastic syndrome; and TBI, total
body irradiation.
*Standard risk for leukemia relapse was defined as the status of the 1st CR of AML and ALL and the 1st CP of CML at transplant, while high risk was defined as a moreadvanced status than standard risk in AML, ALL, and CML, and diseases other than leukemia was defined as other than ALL, ANLL, and CML.

amino acid positions substituted in each HLA locus were analyzed,
amino acid substitutions of any other HLA-A and -C positions were
not significant risk factors. As for HLA-B, DRB1, DQB1, andDPB1, there was no significant association between the positions ofamino acid substitution and severe aGVHD. Impact for OS about
positions and types of amino acid substitutions that were significant
risk factors for aGVHD was shown in Table S9.

Discussion
Extensive recent research has accumulated evidence of the role ofeach HLA locus mismatch on clinical outcome for UR-HSCT.3-9
Our next concern is identifying the combinations of HLA allele
mismatch and the positions of amino acid substitution of the HLA
molecules responsible for aGVHD. In the present study, multivariable analysis revealed that 15 combinations of HLA allele mismatch and 1 HLA-DRB1-DQB1 haplotype mismatch significantly
increase the occurrence of severe aGVHD (Table 2), and most ofthem increased the mortality rate after transplantation (data notshown). Thus, these mismatch combinations of HLA allele might
be called nonpermissive clinically. We speculated that the effect of
HLA locus mismatch was a reflection and summation of these HLA
allele mismatch combinations. Discrepancies of responsible HLA
locus for aGVHD between ethnically diverse transplantations
might be explained by the proportions of nonpermissive mismatch

combinations in each HLA locus. The same study in otherpopulations would be needed to clarify this question as well as theseverity of aGVHD. Interestingly, the full match group and zero
nonpermissive mismatch group showed an almost equal occurrenceof severe aGVHD, though pairs in zero nonpermissive mismatchgroup had one or more mismatches other than nonpermissivemismatches. And HR was elevated with the increase in the numberof nonpermissive mismatches (Figure 1A; Table 4), while thenumber of nonpermissive mismatches also had a significant effecton OS after transplantation (Figure 1B; Table 4). These findings
indicated at least that nonpermissive mismatches should be avoided
in donor selection for UR-HSCT, and that the order of donor
selection based on this nonpermissive mismatch would be useful,instead of that based on HLA locus mismatch. We also speculated
that there are permissive mismatches in mismatches other thannonpermissive mismatches. It is therefore an important task in the
future to identify permissive mismatches for partially HLAmatched donor selection. On the other hand, we do not deny thepossibility that some mismatch combinations not classified as
nonpermissive may actually be potential nonpermissive ones.
Misclassification might happen because of insufficient statisticalpower due to the relatively small number of subjects in
subcategories.
At present, there have been only a few reports indicating that thetransplant-related immunologic reactions and clinical outcomes
were caused by the HLA allele mismatch combinations. Macdonald

BLOOD, 1 OCTOBER 2007 䡠 VOLUME 110, NUMBER 7

HIGH-RISK HLA MISMATCH COMBINATIONS FOR aGVHD

2239

Table 5. Multivariable analysis of impact of amino acid substitution
on HLA class I molecules for severe aGVHD
Posisiton and kindof amino acidsubstitution,
donor-recipient

HS

N

Event†

HR (95% CI)

Tyr9A-Phe9A

4.1

163

64

1.66 (1.19-2.32).003

Asn116A-Asp116A

0

32

15

2.25 (1.26-4.01)

.005*

P

HLA-A locus

HLA-C locus

Figure 1. Impact of number of nonpermissive mismatches on severe aGVHD
and overall survival. (A) Cumulative incidence of severe aGVHD according to
number of nonpermissive mismatches. –– indicates full match (in HLA-A, -B, -C,-DRB1, -DQB1, and -DPB1) group; ----, zero nonpermissive mismatch (with mismatches other than nonpermissive mismatches) group; 䡠 䡠 䡠 䡠, one nonpermissivemismatch (with or without mismatches other than nonpermissive mismatches) group;and – – –, 2 or more nonpermissive mismatches (with or without mismatches otherthan nonpermissive mismatches) group. (B) Kaplan-Meier estimates of survival
according to number of nonpermissive mismatches. Each group was divided as
described for panel A.

et al24 reported that cytotoxic T lymphocytes (CTLs) discriminate
between HLA-B*4402 and HLA-B*4403, and induce strong
alloresponses, but the stronger T-cell alloreactivity is observed
toward HLA-B*4403 compared with HLA-B*4402 in vitro. Zino
et al10 and Fleischhauer et al11 attempted to develop an algorithm
for prediction of nonpermissive HLA-DPB1 mismatches. The
present report is the first to provide far more precise and detailed
evidence for numerous HLA allele mismatch combinations forsevere aGVHD.

Tyr9C-Ser9C

0.5

146

59

1.66 (1.23-2.25).001

Asn77C-Ser77C

2.7

205

90

1.87 (1.46-2.39)⬍ .001

Lys80C-Asn80C

0.4

205

90

1.87 (1.46-2.39)⬍ .001

Tyr99C-Phe99C

4.1

146

59

1.64 (1.21-2.22).001

Leu116C-Ser116C

4.6

53

30

3.40 (2.20-5.25)⬍ .001

Arg156C-Leu156C

8.3

251

88

1.48 (1.15-1.90).002

HLA-B. -DRB1, -DQB1 -DPB1 locus had no significant substitutions. The impact
of positions and types of amino acid substitution in HLA molecules was evaluated inpairs with HLA one-locus mismatch in HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1
separately. For example, Tyr9A-Phe9A indicated amino acid substitutions of position
9 in HLA-A molecule at which donor had tyrosine and patient phenylalanine. The
impacts of positions and kinds of amino acid substitutions in each HLA molecule were
evaluated in pairs with HLA one locus mismatch in each HLA locus separately. Pairs
which substituted specific amino acid at each position were compared with aminoacid matched pairs at that position.
HS indicates hydropathy scale; HR, hazard ratio; CI, confidence interval; Tyr,tyrosine; Phe, phenylalanine; Asn, asparagine; Asp, asparatic acid; Ser, serine; Lys,lysine; Leu, leucine; and Arg, arginine.
*Result of base analysis was significant but result of validating analysis usingbootstrap resampling was not. Results of analysis were thus judged not to bestatistically significant.
†Measured in number of occurrences of severe acute GVHD.

In this study, substitutions of specific amino acids at positions 9,
77, 80, 99, 116, and 156 were elucidated as a significant risk factor
for severe aGVHD. We speculated that the responsibility ofpositions 77 and 80 in HLA-C for severe aGVHD was associatedwith ligand matching of NK-cell receptor (KIR2DL). Although therole of KIR2DL in acute GVHD has been controversial,25 a recent
JMDP analysis demonstrated that KIR2DL ligand mismatchedpairs in GVH vector induced severe aGVHD in UR-HSCT with
T-cell–replete marrow.9 The ligand of KIR2DL is located at
positions 77 and 80, which are completely linked in HLA-C
molecule. And almost all pairs in this study with Asn77C-Ser77C
and Lys80C-Asn80C substitutions have a KIR2DL mismatch in
GVH vector.
Except for positions 77 and 80, which are associated withKIR2DL ligand in HLA-C, positions 9, 99, 116, and 156 were
elucidated. Positions 9, 99, and 116 are located in the beta-plated

Table 4. Multivariable analysis of impact of number of nonpermissive mismatches on severe aGVHD and overall survival
Univariate analysis
N

Event*

HR (95% CI)

Multivariate analysisP

HR (95% CI)

P

Bootstrap (10000)
HR (95% CI)

P

For severe aGVHD
Full match group

972

129

1.00

NA

1.00

NA

1.00

Zero nonpermissive mismatch group

2446

411

1.21 (0.95-1.54).111

1.00 (0.75-1.32).996

1.00 (0.74-1.33)

NA
.996

One nonpermissive mismatch group

571

211

2.88 (2.20-3.78)⬍ .0012.22 (1.62-3.04)⬍ .0012.22 (1.63-3.02)⬍ .001

Two or more nonpermissive mismatch group61

36

5.62 (3.77-8.39)⬍ .001

3.68 (2.33-5.80)⬍ .001

3.68 (2.33-5.80)⬍ .001For overall survival
Full match group

972

400

1.00

NA

1.00

NA

1.00

Zero nonpermissive mismatch group

2446

1021

1.10 (0.98-1.23).091

1.06 (0.94-1.20).315

1.06 (0.94-1.20)

NA
.299

One nonpermissive mismatch group

571

309

1.55 (1.34-1.78)⬍ .0011.51 (1.30-1.76)⬍ .0011.51 (1.29-1.77)⬍ .001

Two or more nonpermissive mismatch group61

39

2.12 (1.54-2.90)⬍ .0012.25 (1.65-3.08)⬍ .0012.25 (1.65-3.08)⬍ .001Each group was compared with Full match group. Confounders considered were sex (donor-recipient pairs), patient age (linear), donor age (linear), type of disease, risk ofleukemia relapse (standard, highand diseases other than leukemia), GVHD prophylaxis, (CSP vs. FK), ATG (ATG vs. no ATG) and preconditioning (TBI vs. non-TBI).
HR indicates hazard ratio; CI, confidence interval; Boot strap (10000), bootstrap resampling using 10000 bootstrapping.
*For severe aGVHD, “Event” refers to number of occurrences; for overall survival, number of deaths.

2240

BLOOD, 1 OCTOBER 2007 䡠 VOLUME 110, NUMBER 7

KAWASE et al

Figure 2. Schematic presentation of HLA class I molecule and summary of features of significant amino acid substituted positions. Numbers in schema of HLA
molecule indicate substituted amino acid positions that were elucidated as significant risk factor for severe aGVHD. Positions 9, 99, and 116 are located in the beta-plated sheet
and positions 77, 80, and 156 in the alpha helix of HLA class I molecule (left). Positions 77 and 80 are associated with KIR2DL ligand in HLA-C molecule. Position 9 constitutes
peptide-binding pockets B and C; position 99 constitutes A, B, and D pockets; position 116 constitutes F pocket; and position 156 constitutes D and E pockets (right). For
example, Tyr-Phe indicated amino acid substitution at indicated position in HLA molecule at which donor had tyrosine and patient phenylalanine. Tyr indicates tyrosine; Phe,phenylalanine; Asn, asparagine; Asp, asparatic acid; Ser, serine; Lys, lysine; Leu, leucine; and Arg, arginine. *Result of base analysis was significant but result of validating
analysis using bootstrap resampling was not. Results of analysis were thus judged not to be statistically significant.

sheet, and position 156 is in the alpha helix of HLA class I molecule(Figure 2).26,27 Position 9 constitutes peptide-binding pockets B
and C, position 99 constitutes A, B, and D pockets, position 116
constitutes F pocket, and position 156 constitutes D and E
pockets.28 As a result, all amino acid positions elucidated in thisstudy were important positions for peptide binding and T-cellrecognition, although all substituted positions including positions
at which residues are not accessible in the vicinity of peptide
binding sites were analyzed.
To our knowledge, amino acid substitutions at position 9(Tyr9A-Phe9A and Tyr9C-Ser9C) and position 99 (Tyr99CPhe99C) were newly identified in the present study as responsible
for severe aGVHD.
Ferrara et al reported that the amino acid substitution at position 116
in HLA class I molecule increased the risk for aGVHD, although thesubstituted amino acid was not taken into consideration.29 In our study,
specific amino acid substitution at position 116 had a significant effect in
HLA-C (Leu116C-Ser116C) and a marginal effect in HLA-A(Asn116AAsp116A) for severe aGVHD (Table 5).
Position 156 of HLA molecule was certified to modify T-cellalloreactivity in vitro in HLA-A2,30-32 HLA-B35,33 and HLA-B44.24
For example, in contrast to Asp156B in HLA-B*4402, the nonpolar
nature of substituted Leu156B in HLA-B*4403 lost many interactions
such as hydrogen bonds and van der Waals interactions with the otheramino acid residues that constructed binding pockets. As a result, thissubstitution made the significant conformation change for alloreactivity.24 In the HLA-B*3501 and HLA-B*3508 combination, Leu156B in
HLA-B*3501 with nonpolar residue was substituted for Asp156B in
HLA-B*3508 with polar residue, and induced strong alloreactivity.33 In
our study, the magnitude of the polar change of each substituted aminoacid was calculated by “hydropathy scale,”17 because the influence of
this scale on the amino acid interaction was much greater than theinfluence of the isoelectric point.34 Specific amino acid substitutions at
position 9, 99, 116, and 156, which were not associated with KIR2DL
ligand, were found to induce great polar changes except for Tyr9CSer9C. Generally speaking, the 3 major physicochemical properties ofamino acids that play important roles in protein structure are thehydropathy scale, isoelectric point, and molecular weight, and molecularweight is reflected in the size of amino acids.34 Indeed, although tyrosine
and serine in Tyr9C-Ser9C show few differences in hydropathy scale
and isoelectric point, their molecular weights are quite different and may
well induce an important conformation change in the HLA molecule.
Thus, the change in the conformation by the polar change of the HLA
molecule might be one of the mechanisms inducing alloreactivity. These
data serve to clarify the mechanisms of aGVHD based on the HLA
molecule.

The analysis of HLA-B, -DRB1, -DPB1, and -DQB1 mismatchfor the substitution of amino acid elucidated no responsible
position for severe aGVHD, and the analysis of HLA-A elucidated
only one position. We speculate that the reason for the above result
in HLA class I was that in this population there were fewer
HLA-mismatched pairs in HLA-A and -B than in HLA-C. Although the findings are due mainly to the HLA-C molecule,specific amino acid substitution at positions 9, 99, 116, and 156 on
the HLA class I molecule may induce strong alloreactivity because
the structures of HLA class I molecules are quite similar.29 Indeed,
position 9 is selected in HLA-A and -C concurrently, and position
116 had a significant effect on HLA-C and a marginal effect on
HLA-A (Figure 2). In HLA class II, we speculated that themolecular base of aGVHD caused by the HLA class II mismatchmight be different from that in HLA class I.
In conclusion, we clarified nonpermissive mismatch combinationsof all major 6 HLA loci. These data would be beneficial for the selectionof suitable donors and international donor exchange for UR-HSCT.
Furthermore, we identified the positions and types of amino acidsubstitutions responsible for severe aGVHD and presented speculations
for alloreactivity on the basis of the conformation change of the HLA
molecule. These findings provide evidence to elucidate the mechanism
of aGVHD on the basis of the HLA molecule.

Acknowledgments
This study was supported in part by Health and Labor Science
Research Grant from Ministry of Health, Labor and Welfare ofJapan (Research on Human Genome, Tissue Engineering), Grantin-Aid B from the Japan Society for the Promotion of Science, anda Grant from Third-Term Comprehensive Control Research forCancer from the Ministry of Health, Labor and Welfare, Japan.
We thank the staff members of the transplant center, donor centers,
and JMDP office for their generous cooperation; Ms Ryouko Yamauchi
for the data management; and Dr Toshitada Takahashi and Dr Setsuko
Kawase for their expert technical assistance.

Authorship
Contribution: T.S., Y.M., T.K., T.J., and Y.K. participated in theconception of this study; K.K., H.I., and H.S. performed theexecution for histocompatibility; Y.M. and S.K. performed theexecution for transplantation; T.K. and K.M. performed statisticalBLOOD, 1 OCTOBER 2007 䡠 VOLUME 110, NUMBER 7

data analysis; T.K. and Y.M. wrote the paper; all authors checked
the final version of the paper.
A complete list of the institutions participating and registering
patients through the Japan Marrow Donor Program for the present
study is available on the Blood website; see the Supplemental
Appendix link at the top of the online article.

HIGH-RISK HLA MISMATCH COMBINATIONS FOR aGVHD

2241

Conflict-of-interest disclosure: The authors declare no competing financial interests.
Correspondence: Yasuo Morishima, Department of Hematology and Cell Therapy, Aichi Cancer Center, 1-1 Kanokoden
chikusa-ku Nagoya 464-8681, Japan; e-mail: ymorisim@aichi-cc.jp.

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2. Kodera Y, Morishima Y, Kato S, et al. Analysis of
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3. Petersdorf EW, Gooley TA, Anasetti C, et al. Optimizing outcome after unrelated marrow transplantation by comprehensive matching of HLAclass I and II alleles in the donor and recipient.
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7. Petersdorf EW, Kollman C, Hurley CK, et al. Effect of HLA class II gene disparity on clinical outcome in unrelated donor hematopoietic cell transplantation for chronic myeloid leukemia: the US
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8. Davies SM, Kollman C, Anasetti C, et al. Engraftment and survival after unrelated-donor bonemarrow transplantation: a report from the national
marrow donor program. Blood. 2000;96:40964102.
9. Morishima Y, Yabe T, Matsuo K, et al. Effects of
HLA allele and killer immunoglobulin-like receptor
ligand matching on clinical outcome in leukemia
patients undergoing transplantation with T-cellreplete marrow from an unrelated donor. Biol
Blood Marrow Transplant. 2007;13:315-328.

10. Zino E, Frumento G, Marktel S, et al. A T-cell
epitope encoded by a subset of HLA-DPB1 alleles determines nonpermissive mismatches forhematologic stem cell transplantation. Blood.
2004;103:1417-1424.

24. Macdonald WA, Purcell AW, Mifsud NA, et al. A
naturally selected dimorphism within the HLAB44 supertype alters class I structure, peptide
repertoire, and T cell recognition. J Exp Med.
2003;198:679-691.

11. Fleischhauer K, Locatelli F, Zecca M, et al. Graftrejection after unrelated donor hematopoietic
stem cell transplantation for thalassemia is associated with nonpermissive HLA-DPB1 disparity in
host-versus-graft direction. Blood. 2006;107:
2984-2992.

25. Parham P. MHC class I molecules and KIRs in
human history, health and survival. Nat Rev Immunol. 2005;5:201-214.

12. Allele Frequencies Database: USA Caucasian
Bethesda, USA Olmstead County Minesota.
Available at: http://www.allelefrequencies.net.
Accessed May 1, 2007.
13. Przepiorka D, Weisdorf D, Martin P, et al. 1994
Consensus Conference on Acute GVHD Grading.
Bone Marrow Transplant. 1995;15:825-828.
14. IMGT/HLA Sequence Database. Available at:
http://www.ebi.ac.uk/imgt/hla/. Accessed February 1, 2007.
15. Socie G. Graft-versus-host disease–from thebench to the bedside? N Engl J Med. 2005;353:
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16. Hansen JA, Gooley TA, Martin PJ, et al. Bonemarrow transplants from unrelated donors for patients with chronic myeloid leukemia. N Engl
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Estimation of failure probabilities in the presenceof competing risks: new representations of oldestimators. Stat Med. 1999;18:695-706.
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20. Cox DR. Regression models and life-tables. J R
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Feinstein AR. A simulation study of the number of
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26. Bjorkman PJ, Saper MA, Samraoui B, Bennett
WS, Strominger JL, Wiley DC. Structure of thehuman class I histocompatibility antigen, HLA-A2.
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Bone marrow transplantation from unrelated donors: the impact of mismatches with substitutionsat position 116 of the human leukocyte antigenclass I heavy chain. Blood. 2001;98:3150-3155.
30. Hogan KT, Clayberger C, Bernhard EJ, et al.
Identification by site-directed mutagenesis ofamino acid residues contributing to serologic and
CTL-defined epitope differences between HLAA2.1 and HLA-A2.3. J Immunol. 1988;141:25192525.
31. Mattson DH, Shimojo N, Cowan EP, et al. Differential effects of amino acid substitutions in thebeta-sheet floor and alpha-2 helix of HLA-A2 on
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1101-1107.
32. Shimojo N, Cowan EP, Engelhard VH, Maloy WL,
Coligan JE, Biddison WE. A single amino acidsubstitution in HLA-A2 can alter the selection of
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33. Tynan FE, Elhassen D, Purcell AW, et al. The immunogenicity of a viral cytotoxic T cell epitope iscontrolled by its MHC-bound conformation. J Exp
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P.28〜41 の日本語版抄録「日本骨髄バンクを介した非血縁者間骨髄移植の成績報告書（2006 年度集計）」より抜粋【T 細胞非除去非血縁者間骨髄移植を受けた白血病患者における HLA 型とKIR リガンド適合度の臨床成績への影響について】

森島泰雄、屋部登志雄、松尾恵太郎、柏瀬貢一、猪子英俊、佐治博夫、山本健、丸屋悦子、
赤塚美樹、鬼塚真、坂巻壽、佐尾浩、小川誠司、加藤俊一、十字猛夫、笹月健彦、小寺良尚、
日本骨髄バンク

日本骨髄バンクを介した白血病移植1790症例におけるHLA座とkiller immunoglobulin-like receptor (KIR)の影響を同時に多変量解析にて調べた。
移植片対白血病効果（GVL）は、白血病の病型により異なっていた。急性リンパ性白血病（ALL）では、HLA-C不適合が、hazard ratio (HR) 0.47, p=0.003)で慢性骨髄性白血病では、HLA-DPB1不適合がHR 0.35, p<0.001で、白血病の再発は有意に低下していた。一方、NK細胞受容体の一つであるKIR２DLのリガンドの不適合（GVH方向）は、ALLにおいて、HR 2.55
p=0.017と白血病の再発率が高まっていた。
移植片の拒絶（2次的正着不全）率は、KIR2DLリガンドの拒絶方向不適合で、HR 4.39
P=0.012と高くなっていた。
急性移植片対宿主病（GVHD）は、HLA-A, B, C, DPB1の各座不適合、ならびにKIR2DLリガ
ンド不適合（GVH方向）で有意に高率であった。
これらの結果として、HLA-A, B, DQB1およびKIR2DLリガンド（GVHD方向）不適合において有意に移植後の生存率が低下していた。
まとめとして、HLA-C, HLA−DPB1およびKIR2DLリガンド不適合が、白血病の再発に関与していたが、白血病の病型により異なっていた。さらに、KIR2DLリガンド不適合は、急性GVHDや拒絶を増加させており、T細胞非除去非血縁者間骨髄移植における生存に対して何ら良い効果を示さなかった。

Biology of Blood and Marrow Transplantation (in press)

27

Biology of Blood and Marrow Transplantation 13:315-328 (2007)䊚 2007 American Society for Blood and Marrow Transplantation
1083-8791/07/1303-0001$32.00/0
doi:10.1016/j.bbmt.2006.10.027

Effects of HLA Allele and Killer Immunoglobulin-Like
Receptor Ligand Matching on Clinical Outcome in
Leukemia Patients Undergoing Transplantation WithT-cell–Replete Marrow From an Unrelated Donor
Yasuo Morishima,1 Toshio Yabe,2 Keitaro Matsuo,3 Koichi Kashiwase,2 Hidetoshi Inoko,4 Hiroh Saji,5
Ken Yamamoto,6 Etsuko Maruya,5 Yoshiki Akatsuka,7 Makoto Onizuka,4 Hisashi Sakamaki,8Hiroshi Sao,9 Seishi Ogawa,10 Shunichi Kato,11 Takeo Juji,12 Takehiko Sasazuki,13 Yoshihisa Kodera,14
for the Japan Marrow Donor Program
1

Aichi Cancer Center Hospital, Department of Hematology and Cell Therapy, Nagoya, Japan; 2Japanese Red Cross
Tokyo Metropolitan Blood Center, Tokyo, Japan; 3Aichi Cancer Center Research Institute, Division of
Epidemiology and Prevention, Nagoya, Japan; 4Tokai University School of Medicine, Division of Molecular
Science, Isehara, Japan; 5HLA Laboratory, NPO, Kyoto, Japan; 6Kyushu University, Medical Institute of
Bioregulation, Department of Molecular Genetics, Fukuoka, Japan; 7Aichi Cancer Center Research Institute,
Division of Immunology, Nagoya, Japan; 8Tokyo Metropolitan Komagome Hospital, Department of Hematology,
Tokyo, Japan; 9Meitetsu Hospital, Department of Hematology, Nagoya, Japan; 10Tokyo University Hospital,
Tokyo, Japan; 11Tokai University School of Medicine, Department of Cell Transplantation and Regenerate
Medicine, Isehara, Japan; 12Japanese Red Cross Central Blood Institute, Tokyo, Japan; 13Japan International
Medical Center of Japan, Tokyo, Japan; 14Japanese Red Cross Nagoya First Hospital, Nagoya, Japan
Correspondence and reprint requests: Yasuo Morishima, MD, Department of Hematology and Cell Therapy, Aichi
Cancer Center Hospital, 1-1 Kanokoden, Chikusa-ku, Nagoya 464-8681, Japan (e-mail: ymorisim@aichi-cc.jp).
Received June 4, 2006; accepted October 26, 2006

ABSTRACTThe responsible human leukocyte antigen (HLA) locus and the role of killer immunoglobulin-like receptor(KIR) ligand matching on transplantation outcome were simultaneously identified by multivariate analysis in1790 patients with leukemia who underwent transplantation with T-cell–replete marrow from an unrelateddonor (UR-BMT) through the Japan Marrow Donor Program. The graft-versus-leukemia (GVL) effectdepended on leukemia cell type. HLA-C mismatch reduced the relapse rate in acute lymphoblastic leukemia(ALL) (hazard ratio [HR] ⴝ 0.47; P ⴝ .003), and HLA-DPB1 mismatch reduced it in chronic myeloid leukemia(CML) (HR ⴝ 0.35; P < .001). In contrast, KIR2DL ligand mismatch in the graft-versus-host (GVH) direction(KIR-L-MM-G) increased in ALL (HR ⴝ 2.55; P ⴝ .017). An increased rejection rate was observed in KIR2DL
ligand mismatch in the host-versus-graft direction (HR ⴝ 4.39; P ⴝ .012). Acute GVH disease (GVHD) was
increased not only in the mismatch of HLA-A, -B, -C, and -DPB1, but also in KIR-L-MM-G. As a whole, themismatch of HLA-A, -B, and -DQB1 locus and KIR-L-MM-G resulted in increased mortality. In conclusion,
not only the mismatch of HLA-C and -DPB1, but also KIR-L-MM-G affected leukemia relapse, which should
be considered based on leukemia cell type. Furthermore, KIR-L-MM induced adverse effects on acute GVHD
(aGVHD) and rejection, and brought no survival benefits to patients with T-cell–replete UR-BMT.
© 2007 American Society for Blood and Marrow Transplantation

KEY WORDSKIR ligand incompatibility

●

HLA

●

INTRODUCTION
Allogeneic hematopoietic stem cell transplantation (HSCT) from a human leukocyte antigen (HLA)-

Leukemia●

Unrelated bone marrow transplantation

matched unrelated (UR) donor has been established as
one mode of curative therapy for hematologic malignancies and other hematologic or immunologic disorders [1,2]. Extensive research on genetic factors such

315

316

as HLA has produced mounting evidence of the presence of HLA alleles that drastically affect HSCT outcome through T cells. Induction of the graft-versusleukemia (GVL) effect to reduce relapse of leukemia isconsidered an advantage of allogeneic HSCT [3].
There have been several large-scale analyses of URHSCT. The Japan Marrow Donor Program(JMDP) demonstrated the effect of matching of
HLA class I alleles (HLA-A, -B, and -C) on thedevelopment of severe acute graft-versus-host disease (aGVHD) and the importance of HLA-A and-B allele matching for better survival in T-cell–
replete UR-HSCT [4,5]. The Fred Hutchinson
Cancer Research Center and the US National Marrow Donor Program (NMDP) reported the importance of HLA class II matching in GVHD andsurvival [6,7]. Updated analysis of the NMDP indicated that HLA-A allele-level mismatching, HLA-B
serologic mismatching, and HLA-DRB1 mismatching are signiﬁcant risk factors for severe aGVHD,
and that disparity in HLA class I (HLA-A, -B, or-C) and/or HLA-DRB1 increased the mortality [8].
Furthermore, the role of HLA-DPB1 matching has
been elucidated for aGVHD [9-11] and leukemia
relapse [12]. However, the aforementioned reports
have produced considerable conﬂicting results.
It has become evident that natural killer (NK) cells
and the subpopulation of T cells express NK cell
receptors, and that the activity of NK cells is controlled by the recognition of HLA class I molecules on
the target cells by NK cell inhibitory and activating
receptors [13,14]. The genotype and haplotype of thekiller immunoglobulin-like receptors (KIRs) havebeen identiﬁed, and ligand speciﬁcities of KIRs havebeen characterized. C1 speciﬁcity of the HLA-C
epitope (Asp80) is the ligand of inhibitory
KIR2DL2/3, C2 speciﬁcity (Lys80) is the ligand of
inhibitory KIR2DL1, and HLA-Bw4 is the ligand of
KIR3DL1. With allogeneic HSCT, the disparities ofthese receptors between donor and recipient are suspected to induce transplant-related immunologic
events through activation of NK cells, and evidence ofthe clinical outcome of HSCT in relation to KIR
disparities has been accumulated [15]. However, reports of KIR ligand matching in UR-HSCT haveshown contradictory results [16]. Limited patientnumbers, different diseases, and various GVHD prophylaxes make it difﬁcult to draw deﬁnite conclusions
from these studies.
In the present study, the effects of HLA locus and
KIR ligand matching were simultaneously analyzed inleukemia patients receiving T-cell–replete marrowfrom unrelated donors through the JMDP after amyeloablative conditioning regimen, focusing in particular on the inﬂuence of leukemia cell type on the
GVL effect.

316

Y. Morishima et al.

PATIENTS AND METHODSPatients

A total of 1790 consecutive leukemia patients who
underwent transplantation with marrow from a serologically HLA-A, -B, and -DR antigen–matched donor in Japan between January 1993 and March 2000
through the JMDP were analyzed. No patients receiving T-cell– depleted marrow and/or antithymocyte
globulin (ATG) as GVHD prophylaxis were eligible
for this study. Partial HLA-A and -B alleles and complete HLA-DRB1 alleles were identiﬁed as conﬁrmatory HLA typing during the coordination process, and
HLA-A, -B, -C, -DQB1, and -DPB1 alleles wereretrospectively reconﬁrmed or identiﬁed after transplantation. The ﬁnal clinical survey of these patientswas completed as of June 1, 2005. Informed consent
was obtained from patient and donor according to the
Declaration of Helsinki, and approval was obtained
from the JMDP and the Institutional Review Board of
the Aichi Cancer Center.
Characteristics of patients and donors are listed inTable 1. The patients’ age ranged from 0 to 59 years(median, 27 years), and donors’ age ranged from 20 to51 years (median, 35 years). There were 577 patientswith acute myeloblastic leukemia (AML), of whom
186 underwent transplantation while in ﬁrst complete
remission (CR), 191 who did so while in second or
further CR, and 200 who did so while in non-CR; 617
patients with acute lymphoblastic leukemia (ALL), ofwhom 236 underwent transplantation while in ﬁrst
CR, 207 who did so while in second or further CR,
and 174 who did so while in non-CR; and 596 patientswith chronic myeloid leukemia (CML), of whom 417
were in the ﬁrst chronic phase (CP), 34 were in thesecond or further CP, 90 were in the accelerated
phase, and 55 were in the blastic phase. Standard risk
for leukemia relapse was deﬁned as the status of theﬁrst CR of AML and ALL and the ﬁrst CP of CML attransplantation, whereas high risk was deﬁned as amore advanced status than standard risk in AML,
ALL, and CML.
HLA Typing of Patients and Donors

Alleles at the HLA-A, -B, -C, -DRB1, -DQB1,
and -DPB1 loci were identiﬁed as described previously [4,5]. HLA 6 locus alleles were typed in 1773
pairs, and HLA 5 locus alleles except HLA-DPB1
were typed in 17 pairs. HLA genotypes of HLA-A, -B,-C, -DQB1, and -DPB1 alleles of patient and donor
were reconﬁrmed by the Luminex microbead method(100 System; Luminex, Austin, TX) adjusted for the
JMDP [17] and in part by the sequencing-based typing method in 2004 and 2005. As a result, all HLA
alleles that were observed with ⬎ 0.1% frequency
among Japanese were identiﬁed. The numbers ofPatient
Number (%)
M/MM*Patient Age
Median (years)
M/MM*

Patient Sex
Female (%)
M/MM*Donor AgeMedian (years)
M/MM*

Donor Sex
Female (%)
M/MM*

Sex
Match (%)
M/MM*

Stage at Transplant
High (%)
M/MM*

GVHD Prophylaxis
Cyclosporine (%)
M/MM*Total Body
Irradiation (%)
M/MM*

27/26
27/26
27/26
27/26
27/26
26/27
26/27
27/25

39/37
40/34
39/41
40/38
40/38
42/39
39/35
39/40

34/33
34/35
34/33
34/34
34/33
34/34
34/34
34/32

38/40
39/36
38/40
38/41
38/41
39/39
39/43
39/60

57/55
56/63
56/58
57/57
57/57
60/56
57/74
57/51

52/57
52/51
52/55
51/60
52/56
50/55
53/63
53/59

73/73
72/76
74/70
74/66
74/67
75/71
73/64
73/67

83/72
83/84
83/82
83/82
83/83
81/84
83/84
83/84

Acute myeloblastic leukemia (n ⴝ 577)
HLA-A
486/91
28/27
HLA-B
537/4027/31
HLA-C
405/172
28/28
HLA-DRB1
474/103
28/27
HLA-DQB1
469/108
27/29
HLA-DPB1
206/366
27/28
KIR2DL-G†
546/31
28/28
KIR2DL-R‡
546/31
28/28

44/44
45/33
43/45
44/43
45/40
48/42
43/55
43/55

33/33
33/35
33/34
33/33
33/33
34/33
33/33
33/35

38/39
39/30
39/37
37/47
38/43
40/38
38/39
38/39

58/55
56/73
56/61
58/55
57/56
58/57
57/65
59/32

67/71
67/83
66/73
66/77
67/72
65/70
67/71
68/68

72/60
71/68
74/63
72/63
72/64
71/70
72/52
71/58

81/89
83/80
82/83
82/86
83/81
81/84
82/83
82/83

Acute lymphoblastic leukemia (n ⴝ 617)
HLA-A
515/102
20/19
HLA-B
567/5019/20
HLA-C
437/180
19/19
HLA-DRB1
485/132
19/19
HLA-DQB1
467/150
19/20
HLA-DPB1
190/425
19/29
KIR2DL-G†
587/3020/17
KIR2DL-R‡
577/40
19/19

41/40
41/42
41/41
41/42
41/41
43/40
42/20
39/40

34/32
33/36
34/32
33/33
34/33
34/33
33/35
34/30

42/42
42/38
41/42
43/36
42/41
38/43
42/40
42/43

55/50
54/60
54/57
55/52
55/51
61/52
55/53
54/53

60/69
61/70
61/63
61/64
61/63
61/62
61/73
61/73

73/74
72/80
73/72
74/70
75/68
77/71
73/73
73/70

91/88
91/86
91/89
90/90
90/92
89/91
91/83
90/93

Chronic myelocytic leukemia (n ⴝ 596)
HLA-A
483/11332/31
HLA-B
541/5532/29
HLA-C
414/182
32/31
HLA-DRB1
475/121
32/33
HLA-DQB1
455/141
32/31
HLA-DPB1
216/372
31/33
KIR2DL-G†
560/3632/32
KIR2DL-R‡
556/40
32/27

33/35
34/27
33/36
34/31
34/33
35/33
34/31
34/28

34/34
34/37
35/34
34/36
35/33
34/35
35/32
35/31

35/40
36/38
35/39
35/40
35/39
38/34
35/50
36/38

59/60
56/60
60/58
58/63
57/65
60/59
59/53
59/65

29/35
29/36
30/31
27/41
28/35
28/31
29/44
29/38

73/81
74/78
74/76
77/64
76/69
76/73
75/67
75/68

76/72
74/85
75/74
76/70
75/74
73/76
71/83
75/75

All leukemia (n ⴝ 1790)
HLA-A
1484/306
HLA-B
1645/145
HLA-C
1256/534
HLA-DRB1
1434/356
HLA-DQB1
1391/399
HLA-DPB1
612/1163
KIR2DL-G†
1693/97
KIR2DL-R‡
1679/111

317

317

Standard-ﬁrst complete remission or ﬁrst chronic phase; high more advanced stage than standard.
*M/MM match/mismatch in GVH direction for HLA matching.
†KIR2DL ligand mismatching in GVH direction.
‡KIR2DL ligand mismatching in HVG direction.

Effect of HLA and KIR Ligand in Leukemia Unrelated-BMT

Table 1. Patient characteristics and matching status of HLA allele and KIR2DL ligand

318

Y. Morishima et al.

identiﬁed alleles in this study were 25 in HLA-A, 43 in
HLA-B, 20 in HLA-C, 33 in HLA-DRB1, 14 in
HLA-DQB1, and 21 in HLA-DPB1.

were a serologic HLA-B match in this study, thecombination of KIR3DL1 and its ligand of Bw4matched in all pairs.

Matching of HLA Allele and KIR2DL Ligand

Definition of Transplantation-Related Events

For the analysis of GVHD and leukemia relapse,
HLA allele mismatch among the donor–recipient pair
was scored when the recipient’s alleles were not sharedby the donor (graft-versus-host [GVH] direction). For
graft rejection, HLA allele mismatch among the donor–recipient pair was scored when the donor’s alleles
were not shared by the patient (host-versus-graft[HVG] direction). For survival, the mismatch was
deﬁned as that of either the GVH direction or the
HVG direction.
KIR2DL ligand speciﬁcity of HLA-C antigen wasdetermined according to the HLA-C allele. The
epitope of HLA-Cw3 group (C1 speciﬁcity) consistsof Asn80, and that of the HLA-Cw4 group (C2 speciﬁcity) consists of Lys80.
KIR ligand mismatch in the GVH direction (KIRL-MM-G) was scored when the donor’s KIR2DL
epitope of HLA-C was not shared by the patient
epitope. This mismatch occurred when KIR2DL2/3or KIR2DL1-positive effector cells were activatedwithout the expression of corresponding HLA-C ligand (C1 or C2, respectively) on the patient’s target
cells. KIR ligand mismatch in HVG direction (KIRL-MM-R) was scored when the patient’s KIR2DL
epitope of HLA-C was not shared by the donor. Thismismatch occurred when patient KIR2DL2/3- or
KIR2DL1-positive effector cells were activated without the expression of corresponding HLA-C ligand(C1 or C2, respectively) on donor cells.

The occurrence of aGVHD was evaluated according to grading criteria in patients who survived morethan 8 days after transplantation, and chronic GVHD
(cGVHD) according to the criteria in patients who
survived more than 100 days after transplantation
as described previously [5]. Rejection was deﬁned
as when the peripheral granulocyte count became⬍ 500/␮L with the ﬁnding of severe hypoplastic marrow in engrafted patients. Engraftment was deﬁned asa peripheral granulocyte count of ⬎ 500/␮L for 3
successive days in patients surviving ⬎ 21 days after
transplantation.

Matching Status of HLA Locus in Allele Level and
KIR2DL Ligand

The matching status of HLA allele matching in
the GVH direction in each HLA locus and KIR ligand
matching in both directions are given in Table 1. The
HLA-C epitope of KIR2DL was estimated from
HLA-C allele type, with 92.4% of the HLA-C allele
belonging to the Cw3 group (C1 speciﬁcity) and 7.6%
belonging to the Cw4 group (C2 speciﬁcity). KIR2DL
ligand match in both directions occurred in 1583 pairs(88.4%). KIR-L-MM-G, which occurred in the combination of KIR2DL ligand in patient– donor pairs,
was found in 97 pairs (5.4%): C1/C1 and C1/C2 in 92
pairs, C2/C2 and C1/C2 in 4 pairs, and C1/C1 andC2/C2 in 1 pair. KIR-L-MM-R, which occurred in
the combination of KIR2DL ligand in patient anddonor pairs, was found in 111 pairs (6.2%): C1/C2and C1/C1 in 105 pairs, C1/C2 and C2/C2 in 5 pairs,
and C1/C1 and C2/C2 in 1 pair. Mismatches in both
directions were found in only 1 pair. Because all pairs

318

GVHD Prophylaxis

Among the 1790 patients transplanted with Tcell–replete marrow, 1302 received a cyclosporinebased regimen and 488 received a tacrolimus-based
regimen for GVHD prophylaxis. Anti-thymocyte
globuline (ATG) was not given for GVHD prophylaxis.
Preconditioning Regimen

All patients were preconditioned with a myeloablative regimen, with 1480 receiving total body irradiation (TBI)-containing regimens and 310 receiving
non-TBI regimens.
Statistical Analysis

All of the analyses were conducted using STATA
version 8.2 (STATA Corp, College Station, TX).
Overall survival rate was assessed by the Kaplan-Meierproduct limit method [18]. Cumulative incidences ofaGVHD, cGVHD, rejection, and leukemia relapse
were assessed as described previously to eliminate theeffect of competing risk [19,20]. The competing
events regarding aGVHD, cGVHD, rejection, andrelapse were deﬁned as death without aGVHD,
cGVHD, rejection, and relapse, respectively. For each
endpoint, a log-rank test was applied to assess theimpact of the factor of interest.
Cox proportional hazard models [21] were applied
to assess the impact of HLA allele matching (mismatch vs match [hazard risk ⫽ 1.0] as a referencegroup) as well as KIR ligand matching (mismatch vsmatch in the GVH direction and mismatch vs matchin the HVG direction) including the following confounders. The confounders considered were sex (donor–recipient pairs), patient age (older: linear), donorage (older: linear), type of disease (AML, CML, orALL), risk of leukemia relapse (high vs standard),

319

Effect of HLA and KIR Ligand in Leukemia Unrelated-BMT

Table 2. Effects of HLA and KIR ligand matching for leukemia relapse
Acute Myeloblastic
Leukemia

All Leukemia Cell Types

HLA-A
HLA-B
HLA-C
HLA-DRB1
HLA-DQB1
HLA-DPB1KIR2DL-G†
KIR2DL-R‡

Acute Lymphoblastic
Leukemia

Chronic Myeloid Leukemia

HR*(95% CI)P

HR(95% CI)P

HR(95% CI)P

HR(95% CI)

P

1.19
1.01
0.71
1.05
1.10
0.68
1.55
0.73

(0.89-1.59)(0.65-1.59)(0.53-0.96)(0.73-1.53)(0.77-1.58)(0.55-0.85)(0.92-2.63)(0.40-1.34)

.251
.953
.025
.789
.579
.001
.103
.313

0.92
1.36
0.8
0.78
1.55
0.76
1.05
0.53

(0.54-1.58)(0.65-2.88)(0.49-1.30)(0.40-1.52)(0.82-2.95)(0.52-1.09)(0.37-3.02)(0.15-1.78)

.761
.416
.366
.466
.178
.137
.926
.305

1.18
0.98
0.47
0.91
1.11
0.92
2.55
1.30

(0.76-1.86)(0.48-1.98)(0.28-0.78)(0.51-1.61)(0.63-1.95)(0.65-1.28)(1.18-5.52)(0.53-3.19)

.462
.952
.003
.737
.71
.604
.017
.569

1.63
0.62
1.2
1.25
0.86
0.35
1.23
0.5

(0.89-2.97)(0.22-1.76)(0.62-2.29)(0.55-2.85)(0.39-1.93)(0.21-0.58)(0.38-3.94)(0.14-1.80)

.114
.367
.591
.59
.72
<.001
.727
.292

HLA matching in GVH direction.
*Hazard ratio of mismatch with match as a reference adjusted for patient age, donor age, sex-matching disease, GVHD prophylaxis, total body
irradiation, transplanted cell dose, risk status, and other matching status of HLA and KIR ligand.
†KIR2DL ligand mismatching in GVH direction.
‡KIR2DL ligand mismatching in HVG direction.

GVHD prophylaxis (tacrolimus-based vs cyclosporine-based and ATG vs cyclosporine-based), numbersof transplanted cells (linear), and preconditioning(non-TBI vs TBI). The numbers of nucleated cells
before manipulation of bone marrow were replacedwith the numbers of transplanted cells.
Multivariate analysis for clinical outcomes, including KIR ligand matching and HLA-C matching in all
pairs (not restricted to HLA-C mismatch), made it
possible to evaluate whether these factors are independent. The results of all pairs by multivariate analysis arepresented in the Results section and in Tables 2, 3, and4. HLA-C–mismatched pairs were selected for the analysis of cumulative incidence in KIR ligand matching.
RESULTS
Effects of HLA Locus Mismatch and KIR Ligand
Mismatch on Leukemia Relapse

When all leukemia patients (AML, ALL, andCML) were analyzed together, HLA-C mismatch was

found to be a factor reducing the relapse rate (HR ⫽0.71; P ⫽ .025) (Table 2). This GVL effect was remarkable in ALL patients (HR ⫽ 0.47; P ⫽ .003),
especially in high risk (HR ⫽ 0.40; P ⫽ .004) but notin standard risk (HR ⫽ 0.85; P ⫽ .728). No such effectwas observed in AML patients (HR ⫽ 0.80; P ⫽ .366)
or CML patients (HR ⫽ 1.20; P ⫽ .591).
Cumulative incidence curves of relapse by leukemia cell type are shown in Figure 1. The relapse rate
5 years after transplantation was 16.7% (95% conﬁdence interval [CI] ⫽ 11.6%-30.9%) for HLA-C mismatch and 29.8% (95% CI ⫽ 25.5%-34.3%) for
HLA-C match in ALL patients (P ⫽ .012); 17.6%(95% CI ⫽ 12.2%-23.8%) and 25.9% (95% CI ⫽21.1%-30.9%), respectively, in AML patients (P ⫽.342); and 11.7% (955 CI ⫽ 12.2%-23.8%) and 12.0%(95% CI ⫽ 9.0%-15.4%), respectively, in CML patients (P ⫽ .485).
HLA-DPB1 mismatch was shown to reduce theoverall leukemia relapse rate (HR ⫽ 0.68; P ⫽ .001)(Table 2). This effect was signiﬁcant in CML (HR ⫽Table 3. Effects of HLA and KIR ligand matching for acute GVHD, chronic GVHD, and rejection in all leukemia cell types

HLA-A
HLA-B
HLA-C
HLA-DRB1
HLA-DQB1
HLA-DPB1KIR2DL-G†
KIR2DL-R‡

Acute GVHD (Grade 2-4)
(n ⴝ 1751)

Acute GVHD (Grade 3-4)
(n ⴝ 1751)

Chronic GVHD(n ⴝ 1109)

Rejection(n ⴝ 1664)

HR*

95% CIPHR

95% CIPHR

95% CIPHR

95% CI

P

1.22
1.43
1.29
1.15
1.02
1.39
1.70
1.04

(1.02-1.46)(1.28-1.82)(1.08-1.55)(0.90-1.47)(0.81-1.29)(1.19-1.63)(1.28-2.26)(0.77-1.42)

.034
.003
.006
.254
.871
<.001
<.001
.78

1.44
1.40
1.39
1.09
1.13
1.26
2.35
1.33

(1.11-1.86)(1.00-1.95)(1.06-1.83)(0.77-1.54)(0.81-1.59)(1.00-1.60)(1.62-3.40)(0.88-2.02)

.006
.05
.017
.644
.465
.053
<.001
.18

1.41
1.00
1.38
0.91
1.20
0.86
1.13
0.88

(1.08-1.85)(0.65-1.52)(1.07-1.78)(0.63-1.31)(0.85-1.69)(0.70-1.05)(0.68-1.87)(0.55-1.42)

.013
.991
.014
.607
.288
.138
.64
.603

0.72
1.16
1.87
0.49
0.62
1.08
0.62
4.39

(0.24-2.14)(0.32-4.16)(0.72-4.86)(0.10-2.33)(0.07-5.16)(0.59-2.41)(0.07-5.16)(1.38-13.96)

.555
.82
.201
.366
.536
.843
.655
.012

HLA matching in GVH direction for acute GVHD and chronic GVHD, and HLA matching in HVG direction for rejection.
*Hazard ratio of mismatch with match as a reference adjusted for patient age, donor age, sex-matching disease, GVHD prophylaxis, total body
irradiation, transplanted cell dose, risk status, and other matching status of HLA and KIR ligand.
†KIR2DL ligand mismatching in GVH direction.
‡KIR2DL ligand mismatching in HVG direction.

319

320

Y. Morishima et al.

Table 4. Effects of HLA and KIR ligand matching for mortality

All Leukemia Cell Types

HLA-A
HLA-B
HLA-C
HLA-DRB1
HLA-DQB1
HLA-DPB1KIR2DL-G†
KIR2DL-R‡

Acute Myeloblastic
Leukemia

Acute Lymphoblastic
Leukemia

Chronic Myeloid Leukemia

HR*

95% CIPHR

95% CIPHR

95% CIPHR

95% CI

P

1.36
1.40
1.17
0.92
1.28
1.06
1.80
1.07

(1.16-1.59)(1.13-1.73)(0.99-1.37)(0.74-1.15)(1.04-1.58)(0.91-1.23)(1.39-2.34)(0.81-1.41)

<.001
.002
.067
.463
.018
.474
<.001
.612

1
1.43
1.18
0.74
1.29
0.96
1.93
1.08

(0.75-1.34)(0.96-2.12)(0.89-1.55)(0.50-1.10)(0.89-1.87)(0.75-1.24)(1.22-3.05)(0.66-1.75)

.978
.079
.246
.136
.184
.772
.005
.769

1.46
1.47
0.99
1.04
1.33
1.33
1.57
0.98

(1.11-1.90)(1.03-2.09)(0.74-1.31)(0.72-1.49)(0.93-1.90)(1.02-1.75)(0.96-2.56)(0.59-1.61)

.006
.036
.928
.849
.108
.038
.069
.934

1.77
1.18
1.42
0.99
1.18
0.97
2.23
1.07

(1.35-2.33)(0.80-1.72)(1.04-1.93)(0.65-1.50)(0.79-1.75)(0.74-1.27)(1.42-3.50)(0.66-1.72)

<.001
.402
.025
.951
.422
.827
<.001
.787

*Hazard ratio of mismatch with match as a reference adjusted for patient age, donor age, sex-matching disease, GVHD prophylaxis, total body
irradiation, transplanted cell dose, risk status, and other matching status of HLA and KIR ligand.
†KIR2DL ligand mismatching in GVH direction.
‡KIR2DL ligand matching in HVG direction.

0.35; P ⬍ .001), and both high-risk and standard-risk
CML had a signiﬁcantly lower relapse rate of HLADPB1 mismatch (HR ⫽ 0.35; P ⬍ .001 and HR ⫽0.39; P ⫽ .012, respectively). No signiﬁcant effectwas observed in AML (HR ⫽ 0.76; P ⫽ .137) or
ALL (HR ⫽ 0.92; P ⫽ .604).

Figure 1. Cumulative incidence of relapse and survival by matching of HLA-C in patients with ALL, AML, and CML. All patients wereanalyzed. The direction of mismatching of HLA-C for relapse is GVH for relapse, and the direction for survival is GVH and/or HVG. The
solid line represents match; the dotted line, mismatch.

320Effect of HLA and KIR Ligand in Leukemia Unrelated-BMT

321

Figure 2. Cumulative incidence of relapse and survival by matching of HLA-DPB1 in patients with ALL, AML, and CML. All patients wereanalyzed. The direction of mismatching of HLA-DPB1 for relapse is GVH for relapse, and the direction for survival is GVH and/or HVG.
Solid line, match; dotted line, mismatch.

As shown in Figure 2, the relapse rate 5 years after
transplantation was 7.1% (95% CI ⫽ 5.0%-10.4%)
for HLA-DPB1 mismatch and 19.3% (95% CI ⫽14.3%-24.9%) for HLA-DPB1 match in CML patients (P ⬍ .001); 20.4% (95% CI ⫽ 16.4%-24.8%)
and 25.9% (95% CI ⫽ 19.9%-32.2%), respectively, in
AML patients (P ⫽ .272); and 24.0% (95% CI ⫽19.9%-28.3%) and 30.2% (95% CI ⫽ 23.7%-37.0%),
respectively, in ALL patients (P ⫽ .319).
Mismatch of HLA-A, -B, -DRB1, and -DQB1 was
not a signiﬁcant risk factor for leukemia relapse bymultivariate analysis (Table 2).
Patients with KIR-L-MM-G had a higher relapse
rate than those with KIR2DL ligand match in ALL(HR ⫽ 2.55; P ⫽ .017) (Table 2). This adverse effecton leukemia relapse was remarkable in high-risk ALL(HR ⫽ 3.03; P ⫽ .013), but not in standard-risk ALL(HR ⫽ 1.11; P ⫽ .921). In AML and CML, KIR-L-

MM-G had no effect on leukemia relapse (HR ⫽ 1.05;
P ⫽ .926 and HR ⫽ 1.23; P ⫽ .727, respectively).
Because KIR-L-MM occurs in HLA-C mismatch
pairs, the cumulative incidence of leukemia relapse
was analyzed in HLA-C mismatch patients in either
direction by leukemia cell type (Figure 3). The relapse
rate 5 years after transplantation was 31.0% (95% CI ⫽5.6%-47.9%) for KIR-L-MM-G and 16.3% (95%CI ⫽ 11.0%-22.4%) for match in ALL patients (P ⫽.026); 11.1% (95% CI ⫽ 3.5%-23.6%) and 11.8%(95% CI ⫽ 7.4%-17.3%), respectively, in CML patients (P ⫽ .634); and 12.9% (95% CI ⫽ 4.1%-27.0%)
and 16.3% (95% CI ⫽ 11.0%-22.6%), respectively, in
AML patients (P ⫽ .757).
Signiﬁcant clinical risk factors for leukemia relapse
by multivariate analysis included status at transplantation (standard vs high, HR ⫽ 3.00; P ⬍ .001) anddisease (HR ⫽ 0.75; P ⬍ .001) in all leukemia patients.

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Y. Morishima et al.

Figure 3. Cumulative incidence of relapse and survival by matching of KIR2DL ligand in the GVH direction in HLA-C–mismatched patientswith ALL, AML, and CML. HLA-C–mismatched patients were selected for this analysis. The directions of HLA-C mismatching were GVH
and/or HVG. The solid line represents KIR2DL ligand match in the GVH direction; the dotted line, KIR2DL mismatch in the GVH
direction.

Effects of HLA Locus Mismatch and KIR Ligand
Mismatch on Rejection

Rejection rates in patients who engrafted marrowand survived more than 21 days were analyzed. KIRL-MM-R was found to be a signiﬁcantly higher risk
factor for rejection compared with match (HR ⫽ 4.39;
P ⫽ .012), and no HLA mismatch was consideredsigniﬁcant by multivariate analysis (Table 3). Olderdonor age was a signiﬁcant clinical risk factor forrejection (HR ⫽ 1.08; P ⫽ .002); other clinical factors
were not signiﬁcant.
The cumulative incidence of graft rejection was
5.7% (95% CI ⫽ 2.3%-11.3%) in KIR-L-MM-R(n ⫽ 106) and 1.8% (95% CI ⫽ 0.8%-3.3%) in match(n ⫽ 447) (P ⫽ .019) 1 year after transplantation in
HLA-C–mismatched patients in either direction. En-

322

graftment rate was not inﬂuenced by HLA and KIR
ligand matching (data not shown).
Effects of HLA Locus Mismatch and KIR Ligand
Mismatch on Acute GVHD

HLA allele mismatch of each HLA-A, -B, and -C
locus was found to be an independent risk factor for
grade 3-4 aGVHD and grade 2-4 aGVHD, and themismatch of each HLA-DRB1 and -DQB1 locus was
not a signiﬁcant risk factor. HLA-DPB1 mismatch
was a signiﬁcant risk factor for grade 2-4 aGVHD anda marginal risk factor for grade 3-4 aGVHD (Table3). When analyzed by leukemia cell type, AML
showed no signiﬁcant HLA mismatch locus for
aGVHD (data not shown).

323

Effect of HLA and KIR Ligand in Leukemia Unrelated-BMT

KIR-L-MM-G was associated with a signiﬁcantly
higher risk of grade 2-4 aGVHD (HR ⫽ 1.70; P ⬍.001) and grade 3-4 aGVHD (HR ⫽ 2.35; P ⬍ .001)
compared with KIR ligand match (Table 3). By leukemia cell type, the HR of KIR-L-MM-G in grade
3-4 aGVHD was 2.76 for AML (P ⫽ .005), 1.75 for
ALL (P ⫽ .111), and 2.79 for CML (P ⬍ .001).
In HLA-C mismatch patients, the incidence of
40.3% in KIR-L-MM-G (95% CI ⫽ 29.3%-50.9%) was
signiﬁcantly higher than the 25.8% in match (95% CI ⫽21.9%-30.0%) (P ⫽ .011) for grade 3-4 aGVHD.
Signiﬁcant clinical risk factors for grade 3-4
GVHD by multivariate analysis were GVHD prophylaxis (tacrolimus vs cyclosporine, HR ⫽ 0.72; P ⫽.016), patient age (HR ⫽ 0.99; P ⫽ .019), donor age(HR ⫽ 1.02; P ⫽ .001), and disease (HR ⫽ 1.28; P ⫽.001) in all leukemia patients.
Effects of HLA Locus Mismatch and KIR Ligand
Mismatch on Chronic GVHD

The occurrence of cGVHD was analyzed in patients who survived more than 100 days after transplantation. HLA-A mismatch and HLA-C mismatch
were found to be signiﬁcant factors (HR ⫽ 1.41; P ⫽.013 and HR ⫽ 1.38; P ⫽ .014, respectively). KIR-LMM-G was not signiﬁcant (HR ⫽ 1.13; P ⫽ .640)(Table 3).
In HLA-C mismatch patients, the cumulative incidence of cGVHD 3 years after transplantation was
43.2% in KIR-L-MM-G (95% CI ⫽ 27.2%-58.3%)
and 40.4% in KIR2DL ligand match (95% CI ⫽35.4%-46.1%) (P ⫽ .727). Signiﬁcant clinical risk factors for cGVHD by multivariate analysis were patientage (HR ⫽ 1.01; P ⫽ .0004), disease (HR ⫽ 1.23; P ⫽.003), and TBI (HR ⫽ 1.54; P ⫽ .004).
Effects of HLA Allele Mismatch and KIR Ligand
Mismatch on Survival

In all leukemia patients, HLA allele mismatch ofeach HLA-A, -B, and -DQB1 locus was found to be an
independent risk factor for mortality after transplantation, and the mismatch of HLA-C was of marginal
risk. HLA mismatch in each HLA-DRB1 and -DPB1
locus was not a signiﬁcant factor. By leukemia cell
type, mismatch of HLA-A, -B, and -DPB1 was asigniﬁcant risk factor in ALL, and mismatch of
HLA-A and -C was a signiﬁcant risk factor in CML(Table 4).
Survival 5 years after transplantation was 39.8% in
HLA-C mismatch (95% CI ⫽ 32.8%-46.7%) and44.5% in HLA-C match (95% CI ⫽ 39.6%-49.3%) in
ALL (P ⫽ .088); 33.7% (95% CI ⫽ 26.9%-40.6%)
and 46.3% (95% CI ⫽ 41.2%-51.2%), respectively, in
AML (P ⬍ .001); and 39.7% (95% CI ⫽ 32.8%46.5%) and 58.3% (95% CI ⫽ 53.2%-63.1%), respectively, in CML (P ⬍ .001) (Figure 1).

Survival 5 years after transplantation was 40.9% in
HLA-DPB1 mismatch (95% CI ⫽ 36.3%-45.4%) and
50.3% in HLA-DPB1 match (95% CI ⫽ 41.5%58.4%) in ALL (P ⫽ .031); 41.8% (95% CI ⫽ 37.0%46.6%) and 42.6% (95% CI ⫽ 34.5%-50.4%), respectively, in AML (P ⫽ .698); and 51.4% (95% CI ⫽46.5%-56.1%) and 53.4% (95% CI ⫽ 45.1%-61.0%),
respectively, in CML (P ⫽ .522) (Figure 2).
KIR-L-MM-G was also found to be a signiﬁcantrisk factor for mortality (HR ⫽ 1.80; P ⬍ .001).
Particularly in AML and CML patients, KIR-L-MM-G
had a signiﬁcantly higher adverse effect than match(HR ⫽ 1.93; P ⫽ .005 and HR ⫽ 2.23; P ⬍ .001,
respectively); its effect was moderate in ALL patients(HR ⫽ 1.57; P ⫽ .069) (Table 4).
In HLA-C mismatch patients in either direction,
the survival rate 5 years after transplantation was
20.0% for KIR-L-MM-G (95% CI ⫽ 6.9%-38.0%)
and 43.0% in match (95% CI ⫽ 35.3%-50.5%) in
ALL (P ⫽ .041); 19.4% (95% CI ⫽ 7.9%-34.6%) and
36.5% (95% CI ⫽ 28.8%-44.2%), respectively, in
AML (P ⫽ .013); and 22.2 (95% CI ⫽ 10.5%-36.7%)
and 43.6% (95% CI ⫽ 35.8%-51.1%), respectively, in
CML (P ⫽ .001) (Figure 3).
Signiﬁcant clinical factors for mortality by multivariate analysis were patient age (HR ⫽ 1.02; P ⬍.001), donor age (HR ⫽ 1.01; P ⫽ .037), disease (HR ⫽0.88; P ⫽ .006), and the status at transplantation (highvs standard, HR ⫽ 2.14; P ⬍ .001).

DISCUSSION
In the present study, we attempted to elucidate
how disparities of HLA and KIR affect leukemia relapse and the other transplantation-related immunologic events and to explore how these ﬁndings can beapplied to induce a GVL effect and improve patient
survival in the unrelated setting. Simultaneous analysis
of HLA and KIR ligand matching by multivariate
analysis made it possible to clarify the role of theseantigens in UR-HSCT.
To the best of our knowledge, this is the ﬁrst
report to elucidate the HLA locus responsible for the
GVL effect by leukemia cell type in T-cell–replete
UR-HSCT. The sequentially registered 577 AML,
617 ALL, and 596 CML patients sufﬁced to analyze
the effects of HLA and KIR ligand matching in the 3
major leukemia cell types.
HLA-C mismatch reduced the relapse rate overall,as reported previously [4]. The GVL effect of HLA-C
mismatch depended on the leukemia cell type. ALL
patients with HLA-C mismatch showed a signiﬁcantly
lower leukemia relapse risk than those with match,whereas AML and CML patients did not. Furthermore, CML patients with HLA-DPB1 mismatch

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324

showed a signiﬁcantly lower leukemia relapse rate
than those with match, whereas AML and ALL patients did not. Although the reason why the HLA
locus responsible for the GVL effect differs with leukemia cell type remains unknown, the different expression of HLA antigens, such as HLA-C, HLADPB1, or co-stimulatory molecules on leukemia cells,
might modify the immune response of effector cells toleukemia cells. The ﬁnding of HLA-DPB1 is in linewith a previous report in CML and ALL patientstreated with T cell– depleted UR-HSCT [12].
In contrast, an impact of HLA-A and -B allele
mismatch on leukemia relapse was not observed. Because HLA-A and/or -B allele mismatch induces severe aGVHD, no GVL effect of HLA-A and /or -B
allele mismatch might imply that the target antigenic
peptide recognized by effector T cells responsible for
aGVHD is not expressed on leukemia cells.
Unexpectedly, KIR-L-MM-G increased the leukemia relapse rate overall. A signiﬁcantly increased
relapse rate in the mismatched group was observed in
ALL, but not in AML and CML. Simultaneous multivariate analysis of HLA-C mismatch and KIR-LMM-G revealed that contrary reactions of these mismatches occurred independently. Although themechanism involved in this detrimental effect of KIRL-MM-G on leukemia relapse is not known, the activation of KIR-positive NK cells or T cells mightcause immune dysfunction, which abrogates the GVL
effect.
The GVL effect of donor-derived KIR-positive
NK cells transplanted puriﬁed CD34⫹ stem cells with
HLA haploidentical donor was reported in AML patients, but not in ALL patients [22]. In T-cell–replete
UR-HSCT, published reports show contradictory effects of KIR ligand mismatch on leukemia relapse. A
GVL effect in myeloid malignancies [23-25], a higher
leukemia relapse rate [26], and no signiﬁcant effect[27-29] all have been reported. The use of ATG for
GVHD prophylaxis might be a key to understanding
these diverse results. Our analysis of T-cell–replete
UR-BMT with no use of ATG provided reliable evidence for the adverse effect of KIR-L-MM-G on
relapse of ALL relapse. No effect on relapse of AML
or CML was reported in a recent large-scale study of
myeloid malignancy from the Center for International
Blood and Marrow Transplant Research, the European Blood and Marrow Transplant Registry, and theDutch Registry [30]. Whether KIR ligand match affects leukemia relapse adversely or beneﬁcially is a
critical issue for clinical transplantation and immunotherapy using NK cells, and further large-scale comparative studies considering GVHD prophylaxis are
warranted.
A higher rejection rate (HR ⫽ 4.39; P ⫽ .012) was
found for KIR-L-MM-R; that is, in this mismatch

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Y. Morishima et al.

combination, patient KIR2DL-positive effector cells
lacking donor KIR ligand are reconstituted and activated after transplantation, which induces the rejection of engrafted donor-derived hematopoietic stem
cells. “Hybrid resistance” has been extensively analyzed in mice to induce graft rejection by NK cells[31]. The same mechanism of rejection induced by
NK cells might be considered in humans, although
88% of KIR ligand mismatch pairs and 86% of match
pairs were given cyclophosphamide as a preconditioning. The effects of HLA class I mismatch for graft
rejection were reported [5,32,33]; our data suggestthat the effect of HLA-C mismatch were mainly because of KIR2DL ligand mismatch in the HVG direction, and may not result from the HLA-C allele
mismatch itself. Our ﬁndings are in agreement with areport showing the effect of rejection but not engraftment by KIR2DL ligand mismatch in UR-HSCT[29].
Since the ﬁrst JMDP report [4], HLA-class I mismatch has been known to signiﬁcantly increase
aGVHD, whereas HLA-DRB1 mismatch has only amarginal effect on aGVHD. The present study has
conﬁrmed those earlier ﬁndings. We could add the
new data on HLA-DPB1 matching showing that
HLA-DPB1 mismatch induces moderate aGVHD.
Our ﬁnding of the effect of HLA-DPB1 on aGVHD
concurs with other reports [9-11], although there wefound no difference in aGVHD between 2 allele mismatches and 1 allele mismatch of HLA-DPB1.
The international collaborative study is expected
to reconcile discrepancies of allele matching in ethnically diverse transplantation populations. Furthermore, the identiﬁcation of nonpermissive HLA allele
mismatch and amino acid substitution responsible for
aGVHD, leukemia relapse, and survival might explainthese discrepancies in diverse ethnic populations.
Interestingly, KIR-L-MM-G had a higher HR ofsevere aGVHD than did match. Because these values
were adjusted by HLA allele matching and clinicalfactors, this ﬁnding demonstrates that KIR-L-MM-G
is a factor independent of HLA allele matching. In
fact, among HLA-C mismatch patients, KIR-LMM-G was associated with a higher rate of grade 3-4
aGVHD than match. In KIR-L-MM-G, the donorderived KIR2DL2/3- or KIR2DL1-positive effector
cells are suspected to react with patient cells that lackthe corresponding KIR2DL epitope of HLA-C.
These effector cells induce aGVHD through several
possible mechanisms. First, NK cells derived fromdonor graft might directly attack the patient target
cells. This is unlikely, however, because in vivo infusion of alloreactive NK cells were found to not cause
aGVHD [34], and NK cells were seen to play mainly
a protective role for GVHD in a murine experimental
model [35]. Alternatively, activated NK cells mightEffect of HLA and KIR Ligand in Leukemia Unrelated-BMT

affect donor-derived T cells that induce aGVHD.
Third, KIR2DL-positive T cells might induce
aGVHD directly. The presence of KIR2DL-positive
T cells was reconstituted after UR-HSCT [36].
Conﬂicting ﬁndings have been reported in termsof the effect of KIR-L-MM-G on aGVHD in T-cell–
replete UR-HSCT. Some studies have found a trend
toward less aGVHD [23], whereas others have reported an increased risk of aGVHD [27,29]. The
variety of GVHD prophylaxis, HLA matching, andother clinical factors, and limited patient numbers ineach study makes it difﬁcult to determine the role of
KIR ligand matching in clinical outcomes. The use of
ATG and/or the T-cell depletion method for GVHD
prophylaxis will be a key strategy in resolving thediscrepancy regarding aGVHD in UR-HSCT [35,37]
and in HLA haplotype–identical related HSCT with
T-cell depletion [38]. That is, T cell and NK-cellreconstitution after transplantation might affect immunologic events induced by the interaction of KIR
and HLA-C epitopes. In addition, genotyping of KIR
genes, especially for activating KIR such as KIR2DS,
is required to understand the mechanism of KIR involved in aGVHD and the GVL effect [39]. The East
Asian population, including Japanese, is known tohave several characteristic HLA types. Similarly, thefrequencies of both the KIR ligand epitope and the
KIR genotype are distinctive in the Japanese population. For example, a higher frequency of C1 epitopeand dominance of the KIR “A” haplotype were reported [40]. Those features might contribute considerably to our results. The combination of KIR2DL1
and C2 epitope has been reported to show higher
afﬁnity and a stronger inhibitory signal compared withthe combination of KIR2DL2/3 and C1 epitope [14].
HLA-A and HLA-C mismatch have been identiﬁed as signiﬁcant independent factors inducing
cGVHD, underscoring our previous ﬁnding of theimportance of HLA class I matching. No inﬂuence of
KIR-L-MM-G on cGVHD (in contrast to aGVHD)
indicates that the KIR-related immunologic reaction
has no relation to cGVHD.
There is another model regarding the KIR ligand
effect in HSCT, the so-called “missing KIR ligand
theory.” Hsu et al reported this effect on survival andrelapse of AML and myelodysplastic syndrome in Tcell– depleted HLA-matched related HSCT [41] andon relapse in AML, ALL, and CML in UR-HSCT in
non-JMDP populations [42]. Lack of either KIR2DL
ligand in a patient should activate the corresponding
donor NK cells and induce the GVL effect.
In the analysis of KIR matching including HLA
mismatch pairs, the mismatch pairs in the “missing
KIR ligand theory” with either C1C1 or C2C2 patient
epitope were divided into match and mismatch in the“KIR ligand matching theory” by donor epitope.

325

When the donor has either C1C1 or C2C2, the KIR
ligand matching theory indicates match, and when thedonor has C1C2, the theory indicates mismatch. In
this combination, donors with C1C2 (n ⫽ 92) had asigniﬁcantly higher rate of severe aGVHD (44.4%)
than donors with either C1C1 or C2C2 (19.2%) (n ⫽1413; P ⬍ .001). Therefore, we considered the “ligand
matching model” to be applied in this JMDP study.
Finally, because survival after transplantation isinﬂuenced not only by leukemia relapse, but also
by transplantation-related mortality resulting fromaGVHD, cGVHD, fatal infections, or graft failure,
the effect of HLA matching and KIR ligand matchingshould be discussed in light of these events.
The present study has more precisely elucidated
the impact of HLA matching on leukemia patient
survival. The mismatch of HLA-A and -B alleles resulted in signiﬁcantly higher mortality. HLA-C andHLA-DQB1 mismatch emerged as a risk factor forpoorer survival for the ﬁrst time in the JMDP study.
Increased survival in ALL with HLA-C mismatchcannot be linked to the compensation from a lower
leukemia relapse rate. HLA-DPB1 mismatch did not
signiﬁcantly affect overall mortality despite the increase in moderately aGVHD. These observations of
HLA-C and -DQB1 mismatch in the JMDP are inline with those of other recent reports. The NMDP
reported an adverse effect of HLA-C mismatch [8],and another study reported that not only HLA-C
mismatch in early-stage CML, but also HLA-DQB1
mismatched CML patients with multiple mismatch
posed increased risk for mortality [43].
It should be noted that KIR-L-MM-G resulted inhigher mortality in UR-HSCT with T-cell–replete
marrow regardless of leukemia cell type. KIR-LMM-G might induce an immunodeﬁcient state thatwould result in a higher risk for opportunistic infections [44,45]. Thus, infectious complications by cytomegalovirus and the like should be explored in relation to KIR.
We estimate that about 30% of patients in theJapanese population have HLA-C mismatch donors,of whom 15.0% are KIR-L-MM in the GVH direction, 20.8% are KIR-L-MM in the HVG direction,and 35.6% are KIR-L-MM in either direction, when
HLA-A, -B, and -DRB1 genotyping is used as thedonor conﬁrmatory typing. Because both KIR2DL
ligand matching and/or HLA matching itself affectaGVHD, cGVHD, rejection, ALL relapse, and survival, as described earlier, HLA-C typing is essential
in selecting a suitable donor to reduce the risk ofaGVHD and improve survival in practice.
In conclusion, our analysis has produced important ﬁndings for transplantation immunology and theselection of donors in UR-HSCT. First, HLA-C andHLA-DPB1 mismatches are expected to induce a ben-

325

326

eﬁcial GVL effect, which should be considered interms of the leukemia cell type of individual patients.
Second, KIR-L-MM should be avoided, because it
induces only adverse effects on transplantation outcome and provides no beneﬁts for patients undergoing
T-cell–replete UR-HSCT.

ACKNOWLEDGMENTS
The authors thank the staff members of the transplant center, donor centers, and JMDP ofﬁce. They
also thank Ms. Ryouko Yamauchi for data management. This work was supported in part by a Healthand Labor Science Research Grant from the Ministryof Health, Labor and Welfare of Japan (Research on
Human Genome, Tissue Engineering); a grant fromCore Research for Evolutional Science and Technology, Japan Science and Technology Corporation;
Grant-in-Aid B (15390309) from the Japan Society for
the Promotion of Science, and a grant (30) fromThird-Term Comprehensive Control Research forCancer from the Ministry of Health, Labor and Welfare, Japan. The institutions participating and registering patients in this study include Hokkaido University Hospital, Sapporo University Hospital,
Sapporo Hokuyu Hospital, Japanese Red Cross Asahikawa Hospital, Asahikawa Medical College Hospital, Hirosaki University Hospital, Iwate Medical University Hospital, Tohoku University Hospital,
Yamagata University Hospital, Akita University Hospital, Fukushima Medical College, Toranomon Hospital, National Cancer Center Central Hospital, National Center for Child Health and Development,
Institute of Medical Science at the University ofTokyo, Toho University Hospital, Omori Hospital,
Tokyo Metropolitan Komagome Hospital, Nihon
University Hospital, Itabashi Hospital, Jikei University Hospital, Keio University Hospital, Tokyo Medical College Hospital, Tokyo Medical and Dental
University Hospital, Tokyo University Hospital,
Yokohama City University Hospital, Kanagawa Children’s Medical Center, Kanagawa Cancer Center,
Tokai University Hospital, St. Marianna University
Hospital, Chiba University Hospital, Chiba Children’s Hospital, Kameda General Hospital, Saitama
Children’s Medical Center, Saitama Cancer Center
Hospital, Saitama Medical School Hospital, Ibaraki
Children’s Hospital, Jichi Medical School Hospital,
Tsukuba University Hospital, Dokkyo University
Hospital, Saiseikai Maebashi Hospital, Gunma University Hospital, Niigata University Hospital, Niigata
Cancer Center Hospital, Shinshu University Hospital,
Hamamatsu University Hospital, Hamamatsu Medical Center, Shizuoka General Hospital, Shizuoka
Children’s Hospital, Japanese Red Cross Nagoya First
Hospital, Nagoya Daini Red Cross Hospital, Meitetsu

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Y. Morishima et al.

Hospital, Nagoya University Hospital, Nagoya Ekisaikai Hospital, Nagoya Medical Center, Aichi Cancer
Center Hospital, Aichi Medical University Hospital,
Nagoya City University Hospital, Showa Hospital,
Anjo Kousei Hospital, Fujita Health University Hospital, Mie University Hospital, Yamada Red Cross
Hospital, Kanazawa University Hospital, Kanazawa
Medical University Hospital, Toyama Prefectural
Central Hospital, Fukui Medical School Hospital,
Shiga University of Medical Science, Center for Adult
Disease in Osaka, Kinki University Hospital, Osaka
University Hospital, Osaka City University Hospital,
Osaka Medical Center and Research Institute for Maternal and Child Health, Matsushita Memorial Hospital, Hyogo College of Medicine Hospital, Hyogo
Medical Center for Adults, Kobe City General Hospital, Kobe University Hospital, Kyoto University
Hospital, Kyoto Prefectural University of Medicine
Hospital, Kyoto City Hospital, Kansai Medical
University Hospital, Tenri Hospital, Nara Medical
University Hospital, Tottori University Hospital,
Hiroshima Red Cross Hospital and Atomic-Bomb
Survivors Hospital, Yamaguchi University Hospital,
Ehime Prefectural Central Hospital, Okayama Medical
Center, Kurashiki Central Hospital, Kyushu University
Hospital, Harasanshin General Hospital, Hamanomachi General Hospital, National Kyushu Cancer Center, St. Mary’s Hospital, Kokura Memorial Hospital,
Nagasaki University Hospital, Kumamoto Medical
Center, Oita Medical University Hospital, Imamura
Hospital, and Kagoshima University Hospital.

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「日本骨髄バンクを介した非血縁者間骨髄移植の成績報告書（2006年度集計）」から抜粋•

スライド１〜４は、DNAレベルでの適合/不適合について解析したものです。

•

また、各ローカス毎のマッチングについての解析では他のローカスが一致した症例のみについて解析されています（例えばHLA-Aの一致、不一致で生存率を比較する場
合にはBとDRが一致した症例のみについて解析）。

•

ここでは、普段、先生方から多く寄せられる質問に関するスライドを掲載しましたが、疾患別等、他の解析結果については、上記報告書をご覧ください。

1.00

１．HLAミスマッチ症例における
急性GVHD Grade3-4発症率0.50

p < 0.0001

0.25

①
②

0.00

Survival Proportion

0.75①不適合 ②適合

0

10

群

20

30

40
50
60
Days after transplantation

症例数

70

発症数

80

90

100

発症率

不適合

2995

677

23±2％

適合

3488

561

16±1％

42

1.00

２．HLA-A locusミスマッチ症例における
急性GVHD Grade3-4発症率0.50

p < 0.0001

①

0.25

Survival Proportion

0.75①不適合 ②適合

0.00

②
0

10

20

30

群

40
50
60
Days after transplantation

症例数

70

80

発症数

90

100

発症率

不適合

572

136

24±4％

適合

3488

561

16±1％

1.00

３．HLA-B locusミスマッチ症例における
急性GVHD Grade3-4発症率0.50

p < 0.0001

0.25

①
②

0.00

Survival Proportion

0.75①不適合 ②適合

0

10

群

20

30

40
50
60
Days after transplantation

症例数

70

80

発症数

90

100

発症率

不適合

203

71

35±7％

適合

3488

561

16±1％

43

1.00

４．HLA-DRB1 locusミスマッチ症例における
急性GVHD Grade3-4発症率0.50

p = 0.0002

①

0.25

Survival Proportion

0.75①不適合 ②適合

0.00

②
0

10

20

30

群

40
50
60
Days after transplantation

症例数

70

80

発症数

90

100

発症率

不適合

1145

236

21±2％

適合

3488

561

16±1％

９．HLA-DR血清学的ミスマッチと遺伝学的
1.00

ミスマッチの比較（急性GVHD grade3-4発症率）
Survival Proportion
0.75
0.50

①DRg適合 ②DRg不適合 ③DRs不適合

p = 0.0008

0.25

③
②

0.00

①
0

10

群

20

30

40
50
60
Days after transplantation

症例数

70

80

発症数

90

100

発症率

DRg適合

2709

388

14±1％

DRg不適合

502

84

16±3％

DRs不適合

195

45

23±6％

（HLA-A,B,C遺伝子型適合症例）

44

1.00

１０．HLA-DR血清学的ミスマッチと遺伝学的ミスマッチの比較（急性GVHD grade2-4発症率）
0.75
0.50

③
②

0.25

①

0.00

p < 0.0001

0

10

20

群

30

40
50
60
Days after transplantation

症例数

70

80

90

発症数

100

発症率

DRg適合

2709

1063

DRg不適合

502

223

38±2％
44±4％

DRs不適合

195

106

54±7％

（HLA-A,B,C遺伝子型適合症例）

1.00

１１．HLA-DR血清学的ミスマッチと遺伝学的ミスマッチの比較（生存率）
0.75①DRg適合 ②DRg不適合 ③DRs不適合

0.50

①
②

0.25

③

p = 0.0003
0.00

Survival Proportion

Survival Proportion①DRg適合 ②DRg不適合 ③DRs不適合

0

1000

群

2000
3000
Days after transplantation

症例数

発症数

4000

3年生存率

５年生存率

DRg適合

2721

1297

70±3％

DRg不適合

514

270

65±8％

60±9％

DRs不適合197

109

46±16％

40±17％（HLA-A,B,C遺伝子型適合症例）

4565±3％