Details

Autor(en) / Beteiligte

• Liu, Yu
• Easton, John
• Shao, Ying
• Maciaszek, Jamie
• Wang, Zhaoming
• Wilkinson, Mark R
• McCastlain, Kelly
• Edmonson, Michael
• Pounds, Stanley B
• Shi, Lei
• Zhou, Xin
• Ma, Xiaotu
• Sioson, Edgar
• Li, Yongjin
• Rusch, Michael
• Gupta, Pankaj
• Pei, Deqing
• Cheng, Cheng
• Smith, Malcolm A
• Auvil, Jaime Guidry
• Gerhard, Daniela S
• Relling, Mary V
• Winick, Naomi J
• Carroll, Andrew J
• Heerema, Nyla A
• Raetz, Elizabeth
• Devidas, Meenakshi
• Willman, Cheryl L
• Harvey, Richard C
• Carroll, William L
• Dunsmore, Kimberly P
• Winter, Stuart S
• Wood, Brent L
• Sorrentino, Brian P
• Downing, James R
• Loh, Mignon L
• Hunger, Stephen P
• Zhang, Jinghui
• Mullighan, Charles G

Titel

The genomic landscape of pediatric and young adult T-lineage acute lymphoblastic leukemia

Ist Teil von

• Nature genetics, 2017-08, Vol.49 (8), p.1211-1218

Ort / Verlag

New York: Nature Publishing Group US

Erscheinungsjahr

2017

Quelle

MEDLINE

Beschreibungen/Notizen

• Charles Mullighan, Stephen Hunger, Jinghui Zhang and colleagues report a genomic analysis of 264 pediatric and young adult T-lineage acute lymphoblastic leukemia (T-ALL) samples. They identify 106 candidate driver genes, 53 of which have not been described previously in pediatric T-ALL, as well as associations between mutations and disease stage or subtype. Genetic alterations that activate NOTCH1 signaling and T cell transcription factors, coupled with inactivation of the INK4/ARF tumor suppressors, are hallmarks of T-lineage acute lymphoblastic leukemia (T-ALL), but detailed genome-wide sequencing of large T-ALL cohorts has not been carried out. Using integrated genomic analysis of 264 T-ALL cases, we identified 106 putative driver genes, half of which had not previously been described in childhood T-ALL (for example, CCND3 , CTCF , MYB , SMARCA4 , ZFP36L2 and MYCN ). We describe new mechanisms of coding and noncoding alteration and identify ten recurrently altered pathways, with associations between mutated genes and pathways, and stage or subtype of T-ALL. For example, NRAS / FLT3 mutations were associated with immature T-ALL, JAK3 / STAT5B mutations in HOXA1 deregulated ALL, PTPN2 mutations in TLX1 deregulated T-ALL, and PIK3R1 / PTEN mutations in TAL1 deregulated ALL, which suggests that different signaling pathways have distinct roles according to maturational stage. This genomic landscape provides a logical framework for the development of faithful genetic models and new therapeutic approaches.