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

Ma X, Edmonson M, Yergeau D, Muzny DM, Hampton OA, Rusch M, Song G, Easton J, Harvey RC, Wheeler DA, Ma J, Doddapaneni H, Vadodaria B, Wu G, Nagahawatte P, Carroll WL, Chen IM, Gastier-Foster JM, Relling MV, Smith MA, Devidas M, Guidry Auvil JM, Downing JR, Loh ML, Willman CL, Gerhard DS, Mullighan CG, Hunger SP, Zhang J - Nat Commun (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Computational Biology, St Jude Children's Research Hospital, Memphis, Tennessee 38105, USA.

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.

No MeSH data available.


Related in: MedlinePlus

Clonal architecture of diagnosis and relapse samples for PAPSPN.(a) Six mutation clusters (marked a–f) constructed from MAF at diagnosis (D; x axis value) and relapse (R; y axis value). Shared mutations are shown in the large square in the centre, while the rectangular areas at the bottom and the left display D- and R-specific mutation clusters, respectively. Each mutation cluster is highlighted in colour with individual mutation marked by an open dot. A mutation in a key pathway is labelled and marked by a solid dot. The MAFs are not normalized by tumour purity. (b) Clonal lineages at diagnosis and relapse. Each clone is identified with a number. Mutation clusters present in each clone are marked by distinct shapes in colours that match those in a. Key mutations as well as CNVs and SVs in each cluster are labelled in the legend. D and R are demarcated by a vertical blue bar. Clonal population size is labelled as percentage of tumour content. The thickness of an arrow from a progenitor clone to its descendant is proportional to population change. ‘Falling’ clones that did not survive therapy are marked by an X. (c) Pattern of rise and fall of subclones from diagnosis to relapse. The legend for the symbols is shown at the right. Remission was marked by dashed lines that separate diagnosis and relapse. Each clone is shown by a circle drawn in proportion to its population size and attached with a bar whose thickness is proportional to mutation burden. A founder clone at D or R is indicated by a solid circle. An inferred founder with population frequency below the detection level (<1%) is marked by a grey box. The clones at D and R are shown in blue and red, respectively. Representive mutations specific to each clonal lineage are marked. A rising clone in relapse that survived therapy is connected to its progenitor at diagnosis by a line.
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f3: Clonal architecture of diagnosis and relapse samples for PAPSPN.(a) Six mutation clusters (marked a–f) constructed from MAF at diagnosis (D; x axis value) and relapse (R; y axis value). Shared mutations are shown in the large square in the centre, while the rectangular areas at the bottom and the left display D- and R-specific mutation clusters, respectively. Each mutation cluster is highlighted in colour with individual mutation marked by an open dot. A mutation in a key pathway is labelled and marked by a solid dot. The MAFs are not normalized by tumour purity. (b) Clonal lineages at diagnosis and relapse. Each clone is identified with a number. Mutation clusters present in each clone are marked by distinct shapes in colours that match those in a. Key mutations as well as CNVs and SVs in each cluster are labelled in the legend. D and R are demarcated by a vertical blue bar. Clonal population size is labelled as percentage of tumour content. The thickness of an arrow from a progenitor clone to its descendant is proportional to population change. ‘Falling’ clones that did not survive therapy are marked by an X. (c) Pattern of rise and fall of subclones from diagnosis to relapse. The legend for the symbols is shown at the right. Remission was marked by dashed lines that separate diagnosis and relapse. Each clone is shown by a circle drawn in proportion to its population size and attached with a bar whose thickness is proportional to mutation burden. A founder clone at D or R is indicated by a solid circle. An inferred founder with population frequency below the detection level (<1%) is marked by a grey box. The clones at D and R are shown in blue and red, respectively. Representive mutations specific to each clonal lineage are marked. A rising clone in relapse that survived therapy is connected to its progenitor at diagnosis by a line.

Mentions: In light of the observed turnover of predominant driver mutations in genes or pathways (Figs 1 and 2), we used deep sequencing data derived from high-coverage WXS and mutation verification data to define clonality. We constructed clonal lineages based on frequency of mutation clusters at diagnosis and relapse8. To improve the precision of the analysis, we developed a binomial mixture model that explicitly accounts for read coverage and determines mutation clusters in three categories: diagnosis specific, relapse specific and shared (see Methods). Clonal architecture for each case is presented in Figs 3, 4, 5 and Supplementary Figs 7–23. Dynamic changes of subclonal population sizes were observed in most of the cases. Here we present three diverse examples to illustrate how clonal evolution resulted in the turnover of the predominant mutations in signalling pathways, the reversal of clonal dominance in a dual-lineage evolution and changes of mutation spectrum after acquiring a relapse-specific mutation in a DNA mismatch repair gene. In these analyses, we refer to three complementary concepts that incorporate MAF, overall mutation load and biological processes at each time point: clusters that use relative MAF at diagnosis and relapse to aggregate multiple mutations; clones that contain multiple clusters constructed by mathematical modelling and lineages that trace clonal rise and fall from ancestral, prediagnosis clones through diagnosis and relapse.


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

Ma X, Edmonson M, Yergeau D, Muzny DM, Hampton OA, Rusch M, Song G, Easton J, Harvey RC, Wheeler DA, Ma J, Doddapaneni H, Vadodaria B, Wu G, Nagahawatte P, Carroll WL, Chen IM, Gastier-Foster JM, Relling MV, Smith MA, Devidas M, Guidry Auvil JM, Downing JR, Loh ML, Willman CL, Gerhard DS, Mullighan CG, Hunger SP, Zhang J - Nat Commun (2015)

Clonal architecture of diagnosis and relapse samples for PAPSPN.(a) Six mutation clusters (marked a–f) constructed from MAF at diagnosis (D; x axis value) and relapse (R; y axis value). Shared mutations are shown in the large square in the centre, while the rectangular areas at the bottom and the left display D- and R-specific mutation clusters, respectively. Each mutation cluster is highlighted in colour with individual mutation marked by an open dot. A mutation in a key pathway is labelled and marked by a solid dot. The MAFs are not normalized by tumour purity. (b) Clonal lineages at diagnosis and relapse. Each clone is identified with a number. Mutation clusters present in each clone are marked by distinct shapes in colours that match those in a. Key mutations as well as CNVs and SVs in each cluster are labelled in the legend. D and R are demarcated by a vertical blue bar. Clonal population size is labelled as percentage of tumour content. The thickness of an arrow from a progenitor clone to its descendant is proportional to population change. ‘Falling’ clones that did not survive therapy are marked by an X. (c) Pattern of rise and fall of subclones from diagnosis to relapse. The legend for the symbols is shown at the right. Remission was marked by dashed lines that separate diagnosis and relapse. Each clone is shown by a circle drawn in proportion to its population size and attached with a bar whose thickness is proportional to mutation burden. A founder clone at D or R is indicated by a solid circle. An inferred founder with population frequency below the detection level (<1%) is marked by a grey box. The clones at D and R are shown in blue and red, respectively. Representive mutations specific to each clonal lineage are marked. A rising clone in relapse that survived therapy is connected to its progenitor at diagnosis by a line.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4377644&req=5

f3: Clonal architecture of diagnosis and relapse samples for PAPSPN.(a) Six mutation clusters (marked a–f) constructed from MAF at diagnosis (D; x axis value) and relapse (R; y axis value). Shared mutations are shown in the large square in the centre, while the rectangular areas at the bottom and the left display D- and R-specific mutation clusters, respectively. Each mutation cluster is highlighted in colour with individual mutation marked by an open dot. A mutation in a key pathway is labelled and marked by a solid dot. The MAFs are not normalized by tumour purity. (b) Clonal lineages at diagnosis and relapse. Each clone is identified with a number. Mutation clusters present in each clone are marked by distinct shapes in colours that match those in a. Key mutations as well as CNVs and SVs in each cluster are labelled in the legend. D and R are demarcated by a vertical blue bar. Clonal population size is labelled as percentage of tumour content. The thickness of an arrow from a progenitor clone to its descendant is proportional to population change. ‘Falling’ clones that did not survive therapy are marked by an X. (c) Pattern of rise and fall of subclones from diagnosis to relapse. The legend for the symbols is shown at the right. Remission was marked by dashed lines that separate diagnosis and relapse. Each clone is shown by a circle drawn in proportion to its population size and attached with a bar whose thickness is proportional to mutation burden. A founder clone at D or R is indicated by a solid circle. An inferred founder with population frequency below the detection level (<1%) is marked by a grey box. The clones at D and R are shown in blue and red, respectively. Representive mutations specific to each clonal lineage are marked. A rising clone in relapse that survived therapy is connected to its progenitor at diagnosis by a line.
Mentions: In light of the observed turnover of predominant driver mutations in genes or pathways (Figs 1 and 2), we used deep sequencing data derived from high-coverage WXS and mutation verification data to define clonality. We constructed clonal lineages based on frequency of mutation clusters at diagnosis and relapse8. To improve the precision of the analysis, we developed a binomial mixture model that explicitly accounts for read coverage and determines mutation clusters in three categories: diagnosis specific, relapse specific and shared (see Methods). Clonal architecture for each case is presented in Figs 3, 4, 5 and Supplementary Figs 7–23. Dynamic changes of subclonal population sizes were observed in most of the cases. Here we present three diverse examples to illustrate how clonal evolution resulted in the turnover of the predominant mutations in signalling pathways, the reversal of clonal dominance in a dual-lineage evolution and changes of mutation spectrum after acquiring a relapse-specific mutation in a DNA mismatch repair gene. In these analyses, we refer to three complementary concepts that incorporate MAF, overall mutation load and biological processes at each time point: clusters that use relative MAF at diagnosis and relapse to aggregate multiple mutations; clones that contain multiple clusters constructed by mathematical modelling and lineages that trace clonal rise and fall from ancestral, prediagnosis clones through diagnosis and relapse.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Computational Biology, St Jude Children's Research Hospital, Memphis, Tennessee 38105, USA.

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.

No MeSH data available.


Related in: MedlinePlus