Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia

Tomoya Isobe; Masatoshi Takagi; Aiko Sato-Otsubo; Akira Nishimura; Genta Nagae; Chika Yamagishi; Moe Tamura; Yosuke Tanaka; Shuhei Asada; Reina Takeda; Akiho Tsuchiya; Xiaonan Wang; Kenichi Yoshida; Yasuhito Nannya; Hiroo Ueno; Ryo Akazawa; Itaru Kato; Takashi Mikami; Kentaro Watanabe; Masahiro Sekiguchi; Masafumi Seki; Shunsuke Kimura; Mitsuteru Hiwatari; Motohiro Kato; Shiro Fukuda; Kenji Tatsuno; Shuichi Tsutsumi; Akinori Kanai; Toshiya Inaba; Yusuke Shiozawa; Yuichi Shiraishi; Kenichi Chiba; Hiroko Tanaka; Rishi S. Kotecha; Mark N. Cruickshank; Fumihiko Ishikawa; Tomohiro Morio; Mariko Eguchi; Takao Deguchi; Nobutaka Kiyokawa; Yuki Arakawa; Katsuyoshi Koh; Yuki Aoki; Takashi Ishihara; Daisuke Tomizawa; Takako Miyamura; Eiichi Ishii; Shuki Mizutani; Nicola K. Wilson; Berthold Göttgens; Satoru Miyano; Toshio Kitamura; Susumu Goyama; Akihiko Yokoyama; Hiroyuki Aburatani; Seishi Ogawa; Junko Takita

doi:10.1038/s41467-022-32266-4

Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia

Tomoya Isobe, Masatoshi Takagi, Aiko Sato-Otsubo, Akira Nishimura, Genta Nagae, Chika Yamagishi, Moe Tamura, Yosuke Tanaka, Shuhei Asada, Reina Takeda, Akiho Tsuchiya, Xiaonan Wang, Kenichi Yoshida, Yasuhito Nannya, Hiroo Ueno, Ryo Akazawa, Itaru Kato, Takashi Mikami, Kentaro Watanabe, Masahiro SekiguchiMasafumi Seki, Shunsuke Kimura, Mitsuteru Hiwatari, Motohiro Kato, Shiro Fukuda, Kenji Tatsuno, Shuichi Tsutsumi, Akinori Kanai, Toshiya Inaba, Yusuke Shiozawa, Yuichi Shiraishi, Kenichi Chiba, Hiroko Tanaka, Rishi S. Kotecha, Mark N. Cruickshank, Fumihiko Ishikawa, Tomohiro Morio, Mariko Eguchi, Takao Deguchi, Nobutaka Kiyokawa, Yuki Arakawa, Katsuyoshi Koh, Yuki Aoki, Takashi Ishihara, Daisuke Tomizawa, Takako Miyamura, Eiichi Ishii, Shuki Mizutani, Nicola K. Wilson, Berthold Göttgens, Satoru Miyano, Toshio Kitamura, Susumu Goyama, Akihiko Yokoyama, Hiroyuki Aburatani, Seishi Ogawa, Junko Takita

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Abstract

KMT2A-rearranged infant acute lymphoblastic leukemia (ALL) represents the most refractory type of childhood leukemia. To uncover the molecular heterogeneity of this disease, we perform RNA sequencing, methylation array analysis, whole exome and targeted deep sequencing on 84 infants with KMT2A-rearranged leukemia. Our multi-omics clustering followed by single-sample and single-cell inference of hematopoietic differentiation establishes five robust integrative clusters (ICs) with different master transcription factors, fusion partners and corresponding stages of B-lymphopoietic and early hemato-endothelial development: IRX-type differentiated (IC1), IRX-type undifferentiated (IC2), HOXA-type MLLT1 (IC3), HOXA-type MLLT3 (IC4), and HOXA-type AFF1 (IC5). Importantly, our deep mutational analysis reveals that the number of RAS pathway mutations predicts prognosis and that the most refractory subgroup of IC2 possesses 100% frequency and the heaviest burden of RAS pathway mutations. Our findings highlight the previously under-appreciated intra- and inter-patient heterogeneity of KMT2A-rearranged infant ALL and provide a rationale for the future development of genomics-guided risk stratification and individualized therapy.

Original language	English
Article number	4501
Journal	Nature Communications
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41467-022-32266-4
Publication status	Published - Dec 2022

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Isobe, T., Takagi, M., Sato-Otsubo, A., Nishimura, A., Nagae, G., Yamagishi, C., Tamura, M., Tanaka, Y., Asada, S., Takeda, R., Tsuchiya, A., Wang, X., Yoshida, K., Nannya, Y., Ueno, H., Akazawa, R., Kato, I., Mikami, T., Watanabe, K., ... Takita, J. (2022). Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia. Nature Communications, 13(1), Article 4501. https://doi.org/10.1038/s41467-022-32266-4

@article{6d67d3b0039b4c6facc0f11686c107ed,

title = "Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia",

abstract = "KMT2A-rearranged infant acute lymphoblastic leukemia (ALL) represents the most refractory type of childhood leukemia. To uncover the molecular heterogeneity of this disease, we perform RNA sequencing, methylation array analysis, whole exome and targeted deep sequencing on 84 infants with KMT2A-rearranged leukemia. Our multi-omics clustering followed by single-sample and single-cell inference of hematopoietic differentiation establishes five robust integrative clusters (ICs) with different master transcription factors, fusion partners and corresponding stages of B-lymphopoietic and early hemato-endothelial development: IRX-type differentiated (IC1), IRX-type undifferentiated (IC2), HOXA-type MLLT1 (IC3), HOXA-type MLLT3 (IC4), and HOXA-type AFF1 (IC5). Importantly, our deep mutational analysis reveals that the number of RAS pathway mutations predicts prognosis and that the most refractory subgroup of IC2 possesses 100% frequency and the heaviest burden of RAS pathway mutations. Our findings highlight the previously under-appreciated intra- and inter-patient heterogeneity of KMT2A-rearranged infant ALL and provide a rationale for the future development of genomics-guided risk stratification and individualized therapy.",

author = "Tomoya Isobe and Masatoshi Takagi and Aiko Sato-Otsubo and Akira Nishimura and Genta Nagae and Chika Yamagishi and Moe Tamura and Yosuke Tanaka and Shuhei Asada and Reina Takeda and Akiho Tsuchiya and Xiaonan Wang and Kenichi Yoshida and Yasuhito Nannya and Hiroo Ueno and Ryo Akazawa and Itaru Kato and Takashi Mikami and Kentaro Watanabe and Masahiro Sekiguchi and Masafumi Seki and Shunsuke Kimura and Mitsuteru Hiwatari and Motohiro Kato and Shiro Fukuda and Kenji Tatsuno and Shuichi Tsutsumi and Akinori Kanai and Toshiya Inaba and Yusuke Shiozawa and Yuichi Shiraishi and Kenichi Chiba and Hiroko Tanaka and Kotecha, {Rishi S.} and Cruickshank, {Mark N.} and Fumihiko Ishikawa and Tomohiro Morio and Mariko Eguchi and Takao Deguchi and Nobutaka Kiyokawa and Yuki Arakawa and Katsuyoshi Koh and Yuki Aoki and Takashi Ishihara and Daisuke Tomizawa and Takako Miyamura and Eiichi Ishii and Shuki Mizutani and Wilson, {Nicola K.} and Berthold G{\"o}ttgens and Satoru Miyano and Toshio Kitamura and Susumu Goyama and Akihiko Yokoyama and Hiroyuki Aburatani and Seishi Ogawa and Junko Takita",

note = "Funding Information: We thank M. Matsumura, N. Hoshino, K. Yin, F. Saito, and S. Shikata for their excellent technical assistance. We are also grateful to the FACS Core at the Institute of Medical Science, The University of Tokyo. This work was supported by the Japan Society of Promotion of Science (JSPS) KAKENHI (nos. JP17H04224, JP18K19467, JP19J11112, JP20H00528 and JP21K19405 to J.T.; no. JP19H05656 to S.O.; no. JP19H03685 to S.G.; and no. JP15K19601 to Y. Aoki); the Japan Agency for Medical Research and Development (AMED) (nos. JP15cm0106056h0005, JP19cm0106501h0004, JP16ck0106073h0003, JP19ck0106250h0003 and JP21cm0106501h0006 to S.O.); AMED Project for Cancer Research and Therapeutic Evolution (P-CREATE) (no. JP20cm0106509h9905 to J.T.; and nos. JP15cm0106139s0202 and JP20cm0106572h0001 to M. Takagi) and Practical Research for Innovative Cancer Control (no. JP20ck0106468h0002 to J.T.); AMED Project for Promotion of Cancer Research and Therapeutic Evolution (P-PROMOTE) (no. JP22ama221505h0001 to J.T.); Grants from the Ministry of Education, Culture, Sports, Science and Technology of Japan (“Program for Promoting Researches on the Supercomputer Fugaku” (Unraveling origin of cancer and diversity by large-scale data analysis and artificial intelligence technology, JPMXP1020200102)) (we used computational resources of supercomputer Fugaku provided by the RIKEN Center for Computational Science (Project ID: hp200138); the High Performance Computing Infrastructure System Research Project (nos. hp160219, hp170227, hp180198 and hp190158 to S.O.) (this research used computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science through the HPCI System Research project); Princess Takamatsu Cancer Research Fund to J.T.; and the Japan Foundation for Pediatric Research (no. 18-001 to T. Isobe). T. Isobe was supported by the Funai Foundation for Information Technology. Funding Information: We thank M. Matsumura, N. Hoshino, K. Yin, F. Saito, and S. Shikata for their excellent technical assistance. We are also grateful to the FACS Core at the Institute of Medical Science, The University of Tokyo. This work was supported by the Japan Society of Promotion of Science (JSPS) KAKENHI (nos. JP17H04224, JP18K19467, JP19J11112, JP20H00528 and JP21K19405 to J.T.; no. JP19H05656 to S.O.; no. JP19H03685 to S.G.; and no. JP15K19601 to Y. Aoki); the Japan Agency for Medical Research and Development (AMED) (nos. JP15cm0106056h0005, JP19cm0106501h0004, JP16ck0106073h0003, JP19ck0106250h0003 and JP21cm0106501h0006 to S.O.); AMED Project for Cancer Research and Therapeutic Evolution (P-CREATE) (no. JP20cm0106509h9905 to J.T.; and nos. JP15cm0106139s0202 and JP20cm0106572h0001 to M. Takagi) and Practical Research for Innovative Cancer Control (no. JP20ck0106468h0002 to J.T.); AMED Project for Promotion of Cancer Research and Therapeutic Evolution (P-PROMOTE) (no. JP22ama221505h0001 to J.T.); Grants from the Ministry of Education, Culture, Sports, Science and Technology of Japan (“Program for Promoting Researches on the Supercomputer Fugaku” (Unraveling origin of cancer and diversity by large-scale data analysis and artificial intelligence technology, JPMXP1020200102)) (we used computational resources of supercomputer Fugaku provided by the RIKEN Center for Computational Science (Project ID: hp200138); the High Performance Computing Infrastructure System Research Project (nos. hp160219, hp170227, hp180198 and hp190158 to S.O.) (this research used computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science through the HPCI System Research project); Princess Takamatsu Cancer Research Fund to J.T.; and the Japan Foundation for Pediatric Research (no. 18-001 to T. Isobe). T. Isobe was supported by the Funai Foundation for Information Technology. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41467-022-32266-4",

language = "English",

volume = "13",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group - Macmillan Publishers",

number = "1",

}

Isobe, T, Takagi, M, Sato-Otsubo, A, Nishimura, A, Nagae, G, Yamagishi, C, Tamura, M, Tanaka, Y, Asada, S, Takeda, R, Tsuchiya, A, Wang, X, Yoshida, K, Nannya, Y, Ueno, H, Akazawa, R, Kato, I, Mikami, T, Watanabe, K, Sekiguchi, M, Seki, M, Kimura, S, Hiwatari, M, Kato, M, Fukuda, S, Tatsuno, K, Tsutsumi, S, Kanai, A, Inaba, T, Shiozawa, Y, Shiraishi, Y, Chiba, K, Tanaka, H, Kotecha, RS , Cruickshank, MN, Ishikawa, F, Morio, T, Eguchi, M, Deguchi, T, Kiyokawa, N, Arakawa, Y, Koh, K, Aoki, Y, Ishihara, T, Tomizawa, D, Miyamura, T, Ishii, E, Mizutani, S, Wilson, NK, Göttgens, B, Miyano, S, Kitamura, T, Goyama, S, Yokoyama, A, Aburatani, H, Ogawa, S & Takita, J 2022, 'Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia', Nature Communications, vol. 13, no. 1, 4501. https://doi.org/10.1038/s41467-022-32266-4

TY - JOUR

T1 - Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia

AU - Isobe, Tomoya

AU - Takagi, Masatoshi

AU - Sato-Otsubo, Aiko

AU - Nishimura, Akira

AU - Nagae, Genta

AU - Yamagishi, Chika

AU - Tamura, Moe

AU - Tanaka, Yosuke

AU - Asada, Shuhei

AU - Takeda, Reina

AU - Tsuchiya, Akiho

AU - Wang, Xiaonan

AU - Yoshida, Kenichi

AU - Nannya, Yasuhito

AU - Ueno, Hiroo

AU - Akazawa, Ryo

AU - Kato, Itaru

AU - Mikami, Takashi

AU - Watanabe, Kentaro

AU - Sekiguchi, Masahiro

AU - Seki, Masafumi

AU - Kimura, Shunsuke

AU - Hiwatari, Mitsuteru

AU - Kato, Motohiro

AU - Fukuda, Shiro

AU - Tatsuno, Kenji

AU - Tsutsumi, Shuichi

AU - Kanai, Akinori

AU - Inaba, Toshiya

AU - Shiozawa, Yusuke

AU - Shiraishi, Yuichi

AU - Chiba, Kenichi

AU - Tanaka, Hiroko

AU - Kotecha, Rishi S.

AU - Cruickshank, Mark N.

AU - Ishikawa, Fumihiko

AU - Morio, Tomohiro

AU - Eguchi, Mariko

AU - Deguchi, Takao

AU - Kiyokawa, Nobutaka

AU - Arakawa, Yuki

AU - Koh, Katsuyoshi

AU - Aoki, Yuki

AU - Ishihara, Takashi

AU - Tomizawa, Daisuke

AU - Miyamura, Takako

AU - Ishii, Eiichi

AU - Mizutani, Shuki

AU - Wilson, Nicola K.

AU - Göttgens, Berthold

AU - Miyano, Satoru

AU - Kitamura, Toshio

AU - Goyama, Susumu

AU - Yokoyama, Akihiko

AU - Aburatani, Hiroyuki

AU - Ogawa, Seishi

AU - Takita, Junko

N1 - Funding Information: We thank M. Matsumura, N. Hoshino, K. Yin, F. Saito, and S. Shikata for their excellent technical assistance. We are also grateful to the FACS Core at the Institute of Medical Science, The University of Tokyo. This work was supported by the Japan Society of Promotion of Science (JSPS) KAKENHI (nos. JP17H04224, JP18K19467, JP19J11112, JP20H00528 and JP21K19405 to J.T.; no. JP19H05656 to S.O.; no. JP19H03685 to S.G.; and no. JP15K19601 to Y. Aoki); the Japan Agency for Medical Research and Development (AMED) (nos. JP15cm0106056h0005, JP19cm0106501h0004, JP16ck0106073h0003, JP19ck0106250h0003 and JP21cm0106501h0006 to S.O.); AMED Project for Cancer Research and Therapeutic Evolution (P-CREATE) (no. JP20cm0106509h9905 to J.T.; and nos. JP15cm0106139s0202 and JP20cm0106572h0001 to M. Takagi) and Practical Research for Innovative Cancer Control (no. JP20ck0106468h0002 to J.T.); AMED Project for Promotion of Cancer Research and Therapeutic Evolution (P-PROMOTE) (no. JP22ama221505h0001 to J.T.); Grants from the Ministry of Education, Culture, Sports, Science and Technology of Japan (“Program for Promoting Researches on the Supercomputer Fugaku” (Unraveling origin of cancer and diversity by large-scale data analysis and artificial intelligence technology, JPMXP1020200102)) (we used computational resources of supercomputer Fugaku provided by the RIKEN Center for Computational Science (Project ID: hp200138); the High Performance Computing Infrastructure System Research Project (nos. hp160219, hp170227, hp180198 and hp190158 to S.O.) (this research used computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science through the HPCI System Research project); Princess Takamatsu Cancer Research Fund to J.T.; and the Japan Foundation for Pediatric Research (no. 18-001 to T. Isobe). T. Isobe was supported by the Funai Foundation for Information Technology. Funding Information: We thank M. Matsumura, N. Hoshino, K. Yin, F. Saito, and S. Shikata for their excellent technical assistance. We are also grateful to the FACS Core at the Institute of Medical Science, The University of Tokyo. This work was supported by the Japan Society of Promotion of Science (JSPS) KAKENHI (nos. JP17H04224, JP18K19467, JP19J11112, JP20H00528 and JP21K19405 to J.T.; no. JP19H05656 to S.O.; no. JP19H03685 to S.G.; and no. JP15K19601 to Y. Aoki); the Japan Agency for Medical Research and Development (AMED) (nos. JP15cm0106056h0005, JP19cm0106501h0004, JP16ck0106073h0003, JP19ck0106250h0003 and JP21cm0106501h0006 to S.O.); AMED Project for Cancer Research and Therapeutic Evolution (P-CREATE) (no. JP20cm0106509h9905 to J.T.; and nos. JP15cm0106139s0202 and JP20cm0106572h0001 to M. Takagi) and Practical Research for Innovative Cancer Control (no. JP20ck0106468h0002 to J.T.); AMED Project for Promotion of Cancer Research and Therapeutic Evolution (P-PROMOTE) (no. JP22ama221505h0001 to J.T.); Grants from the Ministry of Education, Culture, Sports, Science and Technology of Japan (“Program for Promoting Researches on the Supercomputer Fugaku” (Unraveling origin of cancer and diversity by large-scale data analysis and artificial intelligence technology, JPMXP1020200102)) (we used computational resources of supercomputer Fugaku provided by the RIKEN Center for Computational Science (Project ID: hp200138); the High Performance Computing Infrastructure System Research Project (nos. hp160219, hp170227, hp180198 and hp190158 to S.O.) (this research used computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science through the HPCI System Research project); Princess Takamatsu Cancer Research Fund to J.T.; and the Japan Foundation for Pediatric Research (no. 18-001 to T. Isobe). T. Isobe was supported by the Funai Foundation for Information Technology. Publisher Copyright: © 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - KMT2A-rearranged infant acute lymphoblastic leukemia (ALL) represents the most refractory type of childhood leukemia. To uncover the molecular heterogeneity of this disease, we perform RNA sequencing, methylation array analysis, whole exome and targeted deep sequencing on 84 infants with KMT2A-rearranged leukemia. Our multi-omics clustering followed by single-sample and single-cell inference of hematopoietic differentiation establishes five robust integrative clusters (ICs) with different master transcription factors, fusion partners and corresponding stages of B-lymphopoietic and early hemato-endothelial development: IRX-type differentiated (IC1), IRX-type undifferentiated (IC2), HOXA-type MLLT1 (IC3), HOXA-type MLLT3 (IC4), and HOXA-type AFF1 (IC5). Importantly, our deep mutational analysis reveals that the number of RAS pathway mutations predicts prognosis and that the most refractory subgroup of IC2 possesses 100% frequency and the heaviest burden of RAS pathway mutations. Our findings highlight the previously under-appreciated intra- and inter-patient heterogeneity of KMT2A-rearranged infant ALL and provide a rationale for the future development of genomics-guided risk stratification and individualized therapy.

AB - KMT2A-rearranged infant acute lymphoblastic leukemia (ALL) represents the most refractory type of childhood leukemia. To uncover the molecular heterogeneity of this disease, we perform RNA sequencing, methylation array analysis, whole exome and targeted deep sequencing on 84 infants with KMT2A-rearranged leukemia. Our multi-omics clustering followed by single-sample and single-cell inference of hematopoietic differentiation establishes five robust integrative clusters (ICs) with different master transcription factors, fusion partners and corresponding stages of B-lymphopoietic and early hemato-endothelial development: IRX-type differentiated (IC1), IRX-type undifferentiated (IC2), HOXA-type MLLT1 (IC3), HOXA-type MLLT3 (IC4), and HOXA-type AFF1 (IC5). Importantly, our deep mutational analysis reveals that the number of RAS pathway mutations predicts prognosis and that the most refractory subgroup of IC2 possesses 100% frequency and the heaviest burden of RAS pathway mutations. Our findings highlight the previously under-appreciated intra- and inter-patient heterogeneity of KMT2A-rearranged infant ALL and provide a rationale for the future development of genomics-guided risk stratification and individualized therapy.

UR - http://www.scopus.com/inward/record.url?scp=85136937818&partnerID=8YFLogxK

U2 - 10.1038/s41467-022-32266-4

DO - 10.1038/s41467-022-32266-4

M3 - Article

C2 - 36042201

AN - SCOPUS:85136937818

SN - 2041-1723

VL - 13

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 4501

ER -

Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia

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