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1. A new genomic framework to categorize pediatric acute myeloid leukemia.

Author

Umeda, Masayuki, Ma, Jing, Westover, Tamara, Ni, Yonghui, Song, Guangchun, Maciaszek, Jamie, Rusch, Michael, Rahbarinia, Delaram, Foy, Scott, Walsh, Michael, Kumar, Priyadarshini, Liu, Yanling, Yang, Wenjian, Fan, Yiping, Wu, Gang, Baker, Sharyn, Ma, Xiaotu, Wang, Lu, Alonzo, Todd, Rubnitz, Jeffrey, Pounds, Stanley, Klco, Jeffery, and Huang, Benjamin

Subjects
Humans, Child, Leukemia, Myeloid, Acute, Mutation, Prognosis, Genomics, Transcription Factors, Repressor Proteins, Tumor Suppressor Proteins
Abstract

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.

Published
2024

3. Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia.

Author

Farrar, Jason, Smith, Jenny, Othus, Megan, Wang, Yi-Cheng, Ries, Rhonda, Hylkema, Tiffany, Pogosova-Agadjanyan, Era, Challa, Sneha, Leonti, Amanda, Shaw, Timothy, Triche, Timothy, Gamis, Alan, Aplenc, Richard, Kolb, E, Ma, Xiaotu, Stirewalt, Derek, Alonzo, Todd, Meshinchi, Soheil, and Huang, Benjamin

Subjects
Humans, RNA, Long Noncoding, Leukemia, Myeloid, Acute, Prognosis, Treatment Outcome, Mutation
Abstract

PURPOSE: Optimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML. METHODS: To identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis. RESULTS: Training set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays. CONCLUSION: Inclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.

Published
2023

4. Etiology of oncogenic fusions in 5,190 childhood cancers and its clinical and therapeutic implication

Author

Liu, Yanling, Klein, Jonathon, Bajpai, Richa, Dong, Li, Tran, Quang, Kolekar, Pandurang, Smith, Jenny L, Ries, Rhonda E, Huang, Benjamin J, Wang, Yi-Cheng, Alonzo, Todd A, Tian, Liqing, Mulder, Heather L, Shaw, Timothy I, Ma, Jing, Walsh, Michael P, Song, Guangchun, Westover, Tamara, Autry, Robert J, Gout, Alexander M, Wheeler, David A, Wan, Shibiao, Wu, Gang, Yang, Jun J, Evans, William E, Loh, Mignon, Easton, John, Zhang, Jinghui, Klco, Jeffery M, Meshinchi, Soheil, Brown, Patrick A, Pruett-Miller, Shondra M, and Ma, Xiaotu

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Human Genome, Biotechnology, Pediatric Research Initiative, Pediatric Cancer, Rare Diseases, Cancer, Pediatric, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Aetiology, 2.1 Biological and endogenous factors, Humans, Child, Core Binding Factor Alpha 2 Subunit, Oncogene Fusion, Precursor Cell Lymphoblastic Leukemia-Lymphoma, Transcriptome, Causality, Oncogene Proteins, Fusion
Abstract

Oncogenic fusions formed through chromosomal rearrangements are hallmarks of childhood cancer that define cancer subtype, predict outcome, persist through treatment, and can be ideal therapeutic targets. However, mechanistic understanding of the etiology of oncogenic fusions remains elusive. Here we report a comprehensive detection of 272 oncogenic fusion gene pairs by using tumor transcriptome sequencing data from 5190 childhood cancer patients. We identify diverse factors, including translation frame, protein domain, splicing, and gene length, that shape the formation of oncogenic fusions. Our mathematical modeling reveals a strong link between differential selection pressure and clinical outcome in CBFB-MYH11. We discover 4 oncogenic fusions, including RUNX1-RUNX1T1, TCF3-PBX1, CBFA2T3-GLIS2, and KMT2A-AFDN, with promoter-hijacking-like features that may offer alternative strategies for therapeutic targeting. We uncover extensive alternative splicing in oncogenic fusions including KMT2A-MLLT3, KMT2A-MLLT10, C11orf95-RELA, NUP98-NSD1, KMT2A-AFDN and ETV6-RUNX1. We discover neo splice sites in 18 oncogenic fusion gene pairs and demonstrate that such splice sites confer therapeutic vulnerability for etiology-based genome editing. Our study reveals general principles on the etiology of oncogenic fusions in childhood cancer and suggests profound clinical implications including etiology-based risk stratification and genome-editing-based therapeutics.

Published
2023

5. Integrated genomic analysis identifies UBTF tandem duplications as a recurrent lesion in pediatric acute myeloid leukemiaUBTF tandem duplications in pediatric acute myeloid leukemia

Author

Umeda, Masayuki, Ma, Jing, Huang, Benjamin J, Hagiwara, Kohei, Westover, Tamara, Abdelhamed, Sherif, Barajas, Juan M, Thomas, Melvin E, Walsh, Michael P, Song, Guangchun, Tian, Liqing, Liu, Yanling, Chen, Xiaolong, Kolekar, Pandurang, Tran, Quang, Foy, Scott G, Maciaszek, Jamie L, Kleist, Andrew B, Leonti, Amanda R, Ju, Bengsheng, Easton, John, Wu, Huiyun, Valentine, Virginia, Valentine, Marcus B, Liu, Yen-Chun, Ries, Rhonda E, Smith, Jenny L, Parganas, Evan, Iacobucci, Ilaria, Hiltenbrand, Ryan, Miller, Jonathan, Myers, Jason R, Rampersaud, Evadnie, Rahbarinia, Delaram, Rusch, Michael, Wu, Gang, Inaba, Hiroto, Wang, Yi-Cheng, Alonzo, Todd A, Downing, James R, Mullighan, Charles G, Pounds, Stanley, Babu, M Madan, Zhang, Jinghui, Rubnitz, Jeffrey E, Meshinchi, Soheil, Ma, Xiaotu, and Klco, Jeffery M

Subjects
Pediatric Cancer, Pediatric Research Initiative, Clinical Research, Rare Diseases, Cancer, Genetics, Childhood Leukemia, Hematology, Pediatric, 2.1 Biological and endogenous factors, Aetiology, Adult, Child, Chromosome Aberrations, Exons, Genomics, Humans, Leukemia, Myeloid, Acute, Mutation, Recurrence
Abstract

The genetics of relapsed pediatric acute myeloid leukemia (AML) has yet to be comprehensively defined. Here, we present the spectrum of genomic alterations in 136 relapsed pediatric AMLs. We identified recurrent exon 13 tandem duplications (TD) in upstream binding transcription factor (UBTF) in 9% of relapsed AML cases. UBTF-TD AMLs commonly have normal karyotype or trisomy 8 with cooccurring WT1 mutations or FLT3-ITD but not other known oncogenic fusions. These UBTF-TD events are stable during disease progression and are present in the founding clone. In addition, we observed that UBTF-TD AMLs account for approximately 4% of all de novo pediatric AMLs, are less common in adults, and are associated with poor outcomes and MRD positivity. Expression of UBTF-TD in primary hematopoietic cells is sufficient to enhance serial clonogenic activity and to drive a similar transcriptional program to UBTF-TD AMLs. Collectively, these clinical, genomic, and functional data establish UBTF-TD as a new recurrent mutation in AML.SignificanceWe defined the spectrum of mutations in relapsed pediatric AML and identified UBTF-TDs as a new recurrent genetic alteration. These duplications are more common in children and define a group of AMLs with intermediate-risk cytogenetic abnormalities, FLT3-ITD and WT1 alterations, and are associated with poor outcomes. See related commentary by Hasserjian and Nardi, p. 173. This article is highlighted in the In This Issue feature, p. 171.

Published
2022

13. Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia

Author

Huang, Benjamin J, Smith, Jenny L, Farrar, Jason E, Wang, Yi-Cheng, Umeda, Masayuki, Ries, Rhonda E, Leonti, Amanda R, Crowgey, Erin, Furlan, Scott N, Tarlock, Katherine, Armendariz, Marcos, Liu, Yanling, Shaw, Timothy I, Wei, Lisa, Gerbing, Robert B, Cooper, Todd M, Gamis, Alan S, Aplenc, Richard, Kolb, E Anders, Rubnitz, Jeffrey, Ma, Jing, Klco, Jeffery M, Ma, Xiaotu, Alonzo, Todd A, Triche, Timothy, and Meshinchi, Soheil

Subjects
Genetics, Hematology, Rare Diseases, Childhood Leukemia, Human Genome, Stem Cell Research, Cancer, Pediatric, Pediatric Cancer, Pediatric Research Initiative, Clinical Research, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Biomarkers, Child, Gene Expression Profiling, Humans, Leukemia, Myeloid, Acute, Neoplastic Stem Cells, RNA, Recurrence
Abstract

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.

Published
2022

14. CBFB-MYH11 Fusion Transcripts Distinguish Acute Myeloid Leukemias with Distinct Molecular Landscapes and Outcomes

Author

Huang, Benjamin J, Smith, Jenny, Wang, Jim, Taghizadeh, Kassra, Leonti, Amanda R, Ries, Rhonda E, Liu, Yanling, Kolekar, Pandurang, Tarlock, Katherine, Gerbing, Robert B, Crowgey, Erin, Furlan, Scott N, Shaw, Timothy Isham, Hagiwara, Kohei, Wei, Lisa, Cooper, Todd, Gamis, Alan S, Aplenc, Richard, Kolb, Edward A, Farrar, Jason E, Triche, Timothy J, Alonzo, Todd, Ma, Xiaotu, and Meshinchi, Soheil

Subjects
Pediatric Cancer, Biotechnology, Childhood Leukemia, Genetics, Rare Diseases, Cancer, Pediatric, Hematology, Core Binding Factor beta Subunit, Humans, Leukemia, Myeloid, Acute, Myosin Heavy Chains, Oncogene Proteins, Fusion
Abstract

CBFB-MYH11 transcripts and KIT mutations predict relapse in AML. High-risk CBFB-MYH11 transcripts are associated with distinct transcriptional landscapes and upregulation of early hematopoiesis genes.

Published
2021

19. The genomic landscape of pediatric acute lymphoblastic leukemia

Author

Brady, Samuel W., Roberts, Kathryn G., Gu, Zhaohui, Shi, Lei, Pounds, Stanley, Pei, Deqing, Cheng, Cheng, Dai, Yunfeng, Devidas, Meenakshi, Qu, Chunxu, Hill, Ashley N., Payne-Turner, Debbie, Ma, Xiaotu, Iacobucci, Ilaria, Baviskar, Pradyuamna, Wei, Lei, Arunachalam, Sasi, Hagiwara, Kohei, Liu, Yanling, Flasch, Diane A., Liu, Yu, Parker, Matthew, Chen, Xiaolong, Elsayed, Abdelrahman H., Pathak, Omkar, Li, Yongjin, Fan, Yiping, Michael, J. Robert, Rusch, Michael, Wilkinson, Mark R., Foy, Scott, Hedges, Dale J., Newman, Scott, Zhou, Xin, Wang, Jian, Reilly, Colleen, Sioson, Edgar, Rice, Stephen V., Pastor Loyola, Victor, Wu, Gang, Rampersaud, Evadnie, Reshmi, Shalini C., Gastier-Foster, Julie, Guidry Auvil, Jaime M., Gesuwan, Patee, Smith, Malcolm A., Winick, Naomi, Carroll, Andrew J., Heerema, Nyla A., Harvey, Richard C., Willman, Cheryl L., Larsen, Eric, Raetz, Elizabeth A., Borowitz, Michael J., Wood, Brent L., Carroll, William L., Zweidler-McKay, Patrick A., Rabin, Karen R., Mattano, Leonard A., Maloney, Kelly W., Winter, Stuart S., Burke, Michael J., Salzer, Wanda, Dunsmore, Kimberly P., Angiolillo, Anne L., Crews, Kristine R., Downing, James R., Jeha, Sima, Pui, Ching-Hon, Evans, William E., Yang, Jun J., Relling, Mary V., Gerhard, Daniela S., Loh, Mignon L., Hunger, Stephen P., Zhang, Jinghui, and Mullighan, Charles G.

Published
2022
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22. Genomic subtyping and therapeutic targeting of acute erythroleukemia

Author

Iacobucci, Ilaria, Wen, Ji, Meggendorfer, Manja, Choi, John K, Shi, Lei, Pounds, Stanley B, Carmichael, Catherine L, Masih, Katherine E, Morris, Sarah M, Lindsley, R Coleman, Janke, Laura J, Alexander, Thomas B, Song, Guangchun, Qu, Chunxu, Li, Yongjin, Payne-Turner, Debbie, Tomizawa, Daisuke, Kiyokawa, Nobutaka, Valentine, Marcus, Valentine, Virginia, Basso, Giuseppe, Locatelli, Franco, Enemark, Eric J, Kham, Shirley KY, Yeoh, Allen EJ, Ma, Xiaotu, Zhou, Xin, Sioson, Edgar, Rusch, Michael, Ries, Rhonda E, Stieglitz, Elliot, Hunger, Stephen P, Wei, Andrew H, To, L Bik, Lewis, Ian D, D’Andrea, Richard J, Kile, Benjamin T, Brown, Anna L, Scott, Hamish S, Hahn, Christopher N, Marlton, Paula, Pei, Deqing, Cheng, Cheng, Loh, Mignon L, Ebert, Benjamin L, Meshinchi, Soheil, Haferlach, Torsten, and Mullighan, Charles G

Subjects
Agricultural, Veterinary and Food Sciences, Biological Sciences, Bioinformatics and Computational Biology, Genetics, Agricultural Biotechnology, Human Genome, Pediatric, Clinical Research, Rare Diseases, Pediatric Cancer, Orphan Drug, Hematology, Childhood Leukemia, Precision Medicine, Cancer, Biotechnology, Cancer Genomics, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Adolescent, Adult, Child, Child, Preschool, Female, Genomics, Homeodomain Proteins, Humans, Infant, Infant, Newborn, Leukemia, Erythroblastic, Acute, Male, Mutation, Myeloid-Lymphoid Leukemia Protein, Nuclear Proteins, Nucleophosmin, Prognosis, Tumor Suppressor Protein p53, Young Adult, fms-Like Tyrosine Kinase 3, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Acute erythroid leukemia (AEL) is a high-risk leukemia of poorly understood genetic basis, with controversy regarding diagnosis in the spectrum of myelodysplasia and myeloid leukemia. We compared genomic features of 159 childhood and adult AEL cases with non-AEL myeloid disorders and defined five age-related subgroups with distinct transcriptional profiles: adult, TP53 mutated; NPM1 mutated; KMT2A mutated/rearranged; adult, DDX41 mutated; and pediatric, NUP98 rearranged. Genomic features influenced outcome, with NPM1 mutations and HOXB9 overexpression being associated with a favorable prognosis and TP53, FLT3 or RB1 alterations associated with poor survival. Targetable signaling mutations were present in 45% of cases and included recurrent mutations of ALK and NTRK1, the latter of which drives erythroid leukemogenesis sensitive to TRK inhibition. This genomic landscape of AEL provides the framework for accurate diagnosis and risk stratification of this disease, and the rationale for testing targeted therapies in this high-risk leukemia.

Published
2019

27. Understanding the Effects of Bi Modification on the Properties of Ni‐Rich Cathodes.

Author

Meng, Zifei, Hou, Jiahui, Thanwisai, Panya, Fu, Jinzhao, Yao, Zeyi, Zheng, Yadong, Jin, Wenting, Wang, Zexin, Yang, Zhenzhen, Ma, Xiaotu, and Wang, Yan

Subjects
CATHODES, ELECTROCHEMICAL electrodes, ENERGY density, STRUCTURAL stability, ENERGY storage
Abstract

With the skyrocketing market demands for energy storage, lithium ions batteries (LIB) with higher energy density are urgently needed. Cathodes play a critical role in determining the energy density of LIB, and the most popular one is Ni‐rich cathode due to its high capacity. However, due to the fast structural degradation, Ni‐rich cathode materials should be further modified to achieve higher stability. Herein, we introduce bismuth ions in LiNi0.83Co0.11Mn0.06O2 cathodes by adding Bi2O3 during sintering to optimize the specific capacity and cycle stability. By adding 0.1 % mol Bi, the Li+ diffusion and structural stability are effectively optimized, leading to improved electrochemical performances. The modified sample delivers much higher specific capacity (222.9 mAhg−1, 0.05 C) than unmodified sample (204 mAhg−1, 0.05 C). Meanwhile, the specific capacity of optimized sample after 100 cycles at 0.33 C is 27.75 mAhg−1 higher than that of unmodified sample. Therefore, this work demonstrates that Bi modification can be regarded as a possible solution to optimizing the electrochemical performance of Ni‐rich cathodes. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Conditional c-MYC activation in catecholaminergic cells drives distinct neuroendocrine tumors: neuroblastoma vs somatostatinoma

Author

Wang, Tingting, primary, Liu, Lingling, additional, Fang, Jie, additional, Jin, Hongjian, additional, Natarajan, Sivaraman, additional, Sheppard, Heather, additional, Lu, Meifen, additional, Turner, Gregory, additional, Confer, Thomas, additional, Johnson, Melissa, additional, Steinberg, Jeffrey, additional, Ha, Larry, additional, Yadak, Nour, additional, Jain, Richa, additional, Picketts, David J., additional, Ma, Xiaotu, additional, Murphy, Andrew, additional, Davidoff, Andrew M., additional, Glazer, Evan S., additional, Easton, John, additional, Chen, Xiang, additional, Wang, Ruoning, additional, and Yang, Jun, additional

Published
2024
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29. Recycled cathode materials enabled superior performance for lithium-ion batteries

Author

Ma, Xiaotu, Chen, Mengyuan, Zheng, Zhangfeng, Bullen, Dennis, Wang, Jun, Harrison, Chloe, Gratz, Eric, Lin, Yulin, Yang, Zhenzhen, Zhang, Youtian, Wang, Fan, Robertson, David, Son, Seoung-Bum, Bloom, Ira, Wen, Jianguo, Ge, Mingyuan, Xiao, Xianghui, Lee, Wah-Keat, Tang, Ming, Wang, Qiang, Fu, Jinzhao, Zhang, Yubin, Sousa, Bryer C., Arsenault, Renata, Karlson, Peter, Simon, Nakia, and Wang, Yan

Published
2021
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30. UBTF tandem duplications in pediatric myelodysplastic syndrome and acute myeloid leukemia: implications for clinical screening and diagnosis

Author

Barajas, Juan M., primary, Umeda, Masayuki, additional, Contreras, Lisett, additional, Khanlari, Mahsa, additional, Westover, Tamara, additional, Walsh, Michael P., additional, Xiong, Emily, additional, Yang, Chenchen, additional, Otero, Brittney, additional, Arribas-Layton, Marc, additional, Abdelhamed, Sherif, additional, Song, Guangchun, additional, Ma, Xiaotu, additional, Thomas 3rd, Melvin E., additional, Ma, Jing, additional, and Klco, Jeffery M., additional

Published
2024
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32. Chemotherapy and mismatch repair deficiency cooperate to fuel TP53 mutagenesis and ALL relapse

Author

Yang, Fan, Brady, Samuel W., Tang, Chao, Sun, Huiying, Du, Lijuan, Barz, Malwine J., Ma, Xiaotu, Chen, Yao, Fang, Houshun, Li, Xiaomeng, Kolekar, Pandurang, Pathak, Omkar, Cai, Jiaoyang, Ding, Lixia, Wang, Tianyi, von Stackelberg, Arend, Shen, Shuhong, Eckert, Cornelia, Klco, Jeffery M., Chen, Hongzhuan, Duan, Caiwen, Liu, Yu, Li, Hui, Li, Benshang, Kirschner-Schwabe, Renate, Zhang, Jinghui, and Zhou, Bin-Bing S.

Published
2021
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35. Bacteria-derived nanovesicles enhance tumour vaccination by trained immunity

Author

Liu, Guangna, primary, Ma, Nana, additional, Cheng, Keman, additional, Feng, Qingqing, additional, Ma, Xiaotu, additional, Yue, Yale, additional, Li, Yao, additional, Zhang, Tianjiao, additional, Gao, Xiaoyu, additional, Liang, Jie, additional, Zhang, Lizhuo, additional, Wang, Xinwei, additional, Ren, Zhenhua, additional, Fu, Yang-Xin, additional, Zhao, Xiao, additional, and Nie, Guangjun, additional

Published
2023
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36. SJPedPanel: A pan-cancer gene panel for childhood malignancies

Author

Kolekar, Pandurang, primary, Balagopal, Vidya, additional, Dong, Li, additional, Liu, Yanling, additional, Foy, Scott, additional, Tran, Quang, additional, Mulder, Heather, additional, Huskey, Anna LW, additional, Plyler, Emily, additional, Liang, Zhikai, additional, Ma, Jingqun, additional, Nakitandwe, Joy, additional, Gu, Jiali, additional, Maciaszek, Jamie, additional, Payne-Turner, Debbie, additional, Mallampati, Saradhi, additional, Wang, Lu, additional, Stewart, Elizabeth, additional, Easton, John, additional, Klco, Jeffery M, additional, and Ma, Xiaotu, additional

Published
2023
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37. UBTFTandem Duplications in Pediatric MDS and AML: Implications for Clinical Screening and Diagnosis

Author

Barajas, Juan M., primary, Umeda, Masayuki, additional, Contreras, Lisett, additional, Khanlari, Mahsa, additional, Westover, Tamara, additional, Walsh, Michael P., additional, Xiong, Emily, additional, Yang, Chenchen, additional, Otero, Brittney, additional, Arribas-Layton, Marc, additional, Abdelhamed, Sherif, additional, Song, Guangchun, additional, Ma, Xiaotu, additional, Thomas, Melvin E., additional, Ma, Jing, additional, and Klco, Jeffery M., additional

Published
2023
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39. Integrative network analysis reveals USP7 haploinsufficiency inhibits E-protein activity in pediatric T-lineage acute lymphoblastic leukemia (T-ALL)

Author

Shaw, Timothy I., Dong, Li, Tian, Liqing, Qian, Chenxi, Liu, Yu, Ju, Bensheng, High, Anthony, Kavdia, Kanisha, Pagala, Vishwajeeth R., Shaner, Bridget, Pei, Deqing, Easton, John, Janke, Laura J., Porter, Shaina N., Ma, Xiaotu, Cheng, Cheng, Pruett-Miller, Shondra M., Choi, John, Yu, Jiyang, Peng, Junmin, Gu, Wei, Look, A. Thomas, Downing, James R., and Zhang, Jinghui

Published
2021
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42. The acquisition of molecular drivers in pediatric therapy-related myeloid neoplasms

Author

Schwartz, Jason R., Ma, Jing, Kamens, Jennifer, Westover, Tamara, Walsh, Michael P., Brady, Samuel W., Robert Michael, J., Chen, Xiaolong, Montefiori, Lindsey, Song, Guangchun, Wu, Gang, Wu, Huiyun, Branstetter, Cristyn, Hiltenbrand, Ryan, Walsh, Michael F., Nichols, Kim E., Maciaszek, Jamie L., Liu, Yanling, Kumar, Priyadarshini, Easton, John, Newman, Scott, Rubnitz, Jeffrey E., Mullighan, Charles G., Pounds, Stanley, Zhang, Jinghui, Gruber, Tanja, Ma, Xiaotu, and Klco, Jeffery M.

Published
2021
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46. Rise and fall of subclones from diagnosis to relapse in pediatric B-acute lymphoblastic leukaemia.

Author

Ma, Xiaotu, Edmonson, Michael, Yergeau, Donald, Muzny, Donna M, Hampton, Oliver A, Rusch, Michael, Song, Guangchun, Easton, John, Harvey, Richard C, Wheeler, David A, Ma, Jing, Doddapaneni, HarshaVardhan, Vadodaria, Bhavin, Wu, Gang, Nagahawatte, Panduka, Carroll, William L, Chen, I-Ming, Gastier-Foster, Julie M, Relling, Mary V, Smith, Malcolm A, Devidas, Meenakshi, Guidry Auvil, Jaime M, Downing, James R, Loh, Mignon L, Willman, Cheryl L, Gerhard, Daniela S, Mullighan, Charles G, Hunger, Stephen P, and Zhang, Jinghui

Subjects
Clone Cells, Humans, Neoplasm Recurrence, Local, Disease Progression, GTP Phosphohydrolases, 5'-Nucleotidase, Histone-Lysine N-Methyltransferase, Membrane Proteins, Extracellular Matrix Proteins, Repressor Proteins, Mutation, Child, Female, Male, Tumor Suppressor Protein p53, CREB-Binding Protein, Ikaros Transcription Factor, Precursor B-Cell Lymphoblastic Leukemia-Lymphoma, DNA Copy Number Variations, Exome, Clonal Evolution, Neoplasm Recurrence, Local, 5-Nucleotidase
Abstract

There is incomplete understanding of genetic heterogeneity and clonal evolution during cancer progression. Here we use deep whole-exome sequencing to describe the clonal architecture and evolution of 20 pediatric B-acute lymphoblastic leukaemias from diagnosis to relapse. We show that clonal diversity is comparable at diagnosis and relapse and clonal survival from diagnosis to relapse is not associated with mutation burden. Six pathways were frequently mutated, with NT5C2, CREBBP, WHSC1, TP53, USH2A, NRAS and IKZF1 mutations enriched at relapse. Half of the leukaemias had multiple subclonal mutations in a pathway or gene at diagnosis, but mostly with only one, usually minor clone, surviving therapy to acquire additional mutations and become the relapse founder clone. Relapse-specific mutations in NT5C2 were found in nine cases, with mutations in four cases being in descendants of the relapse founder clone. These results provide important insights into the genetic basis of treatment failure in ALL and have implications for the early detection of mutations driving relapse.

Published
2015

50. Outer Membrane Vesicle‐Based Nanohybrids Target Tumor‐Associated Macrophages to Enhance Trained Immunity‐Related Vaccine‐Generated Antitumor Activity

Author

Liang, Jie, primary, Zhu, Fei, additional, Cheng, Keman, additional, Ma, Nana, additional, Ma, Xiaotu, additional, Feng, Qingqing, additional, Xu, Chen, additional, Gao, Xiaoyu, additional, Wang, Xinwei, additional, Shi, Jian, additional, Zhao, Xiao, additional, and Nie, Guangjun, additional

Published
2023
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