Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia.
Single-cell genotyping demonstrates complex clonal diversity in acute myeloid leukemia.
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单细胞基因分型证明了急性髓系白血病复杂的克隆多样性。
DOI:
10.1126/scitranslmed.aaa0763
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发表时间:
2015-04-01
影响因子:
17.1
通讯作者:
Radich JP
中科院分区:
文献类型:
--
作者:
Paguirigan AL;Smith J;Meshinchi S;Carroll M;Maley C;Radich JP
Clonal evolution in cancer – the selection for and emergence of increasingly malignant clones during progression and therapy, resulting in cancer metastasis and relapse – has been highlighted as an important phenomenon in the biology of leukemia and other cancers. Tracking mutant alleles to determine clonality from diagnosis to relapse, or primary site to metastases, in a sensitive and quantitative manner is most often performed using next generation sequencing. Such methods determine clonal frequencies by extrapolation of allele frequencies in sequencing data of DNA from the metagenome of bulk tumor samples using a set of assumptions. The computational framework that is usually employed assumes specific patterns in the order of acquisition of unique mutational events and heterozygosity of mutations in single cells. However, these assumptions are not accurate for all mutant loci in acute myeloid leukemia (AML) samples. In order to assess whether current models of clonal diversity within individual AML samples are appropriate for common mutations, we developed protocols to directly genotype AML single cells. Single cell analysis demonstrates that mutations of FLT3 and NPM1 occur in both homozygous and heterozygous states, distributed among at least 9 distinct clonal populations in all samples analyzed. There appears to be convergent evolution and differential evolutionary trajectories for cells containing mutations at different loci. This work suggests an underlying tumor heterogeneity beyond what is currently understood in AML, which may be important in the development of therapeutic approaches to eliminate leukemic cell burden and control clonal evolution-induced relapse.
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影响因子:
64.5
作者:
Welch JS;Ley TJ;Link DC;Miller CA;Larson DE;Koboldt DC;Wartman LD;Lamprecht TL;Liu F;Xia J;Kandoth C;Fulton RS;McLellan MD;Dooling DJ;Wallis JW;Chen K;Harris CC;Schmidt HK;Kalicki-Veizer JM;Lu C;Zhang Q;Lin L;O'Laughlin MD;McMichael JF;Delehaunty KD;Fulton LA;Magrini VJ;McGrath SD;Demeter RT;Vickery TL;Hundal J;Cook LL;Swift GW;Reed JP;Alldredge PA;Wylie TN;Walker JR;Watson MA;Heath SE;Shannon WD;Varghese N;Nagarajan R;Payton JE;Baty JD;Kulkarni S;Klco JM;Tomasson MH;Westervelt P;Walter MJ;Graubert TA;DiPersio JF;Ding L;Mardis ER;Wilson RK
通讯作者:
Wilson RK
影响因子:
64.8
作者:
Greaves, Mel;Maley, Carlo C.
通讯作者:
Maley, Carlo C.
影响因子:
20.3
作者:
Thiede, C;Steudel, C;Illmer, T
通讯作者:
Illmer, T
影响因子:
8
作者:
Jan M;Majeti R
通讯作者:
Majeti R
影响因子:
20.3
作者:
Keats, Jonathan J.;Chesi, Marta;Bergsagel, P. Leif
通讯作者:
Bergsagel, P. Leif