A TARGETED SEQUENCING APPROACH IN MULTIPLE MYELOMA REVEALS A COMPLEX LANDSCAPE OF GENOMIC LESIONS THAT HAS IMPLICATIONS FOR PROGNOSIS
(Abstract release date: 05/19/16)
EHA Library. Bolli N. 06/11/16; 135203; S447
Prof. Niccolò Bolli
Contributions
Contributions
Abstract
Abstract: S447
Type: Oral Presentation
Presentation during EHA21: On Saturday, June 11, 2016 from 11:30 - 11:45
Location: Auditorium 2
Background
Next-generation sequencing (NGS) studies have shown that multiple myeloma is a heterogeneous disease with a complex subclonal architecture and few recurrently mutated genes. The analysis of smaller regions of interest in the genome (“targeted studies”) allows interrogation of recurrent genomic events with reduces complexity of downstream analysis at a lower price.
Aims
Here, we performed the largest targeted study to date in multiple myeloma to analyze gene mutations, deletions and amplifications, chromosomal copy number changes and immunoglobulin heavy chain locus (IGH) translocations and correlate results with biological and clinical features.
Methods
We used Agilent SureSelect cRNA pull down baits to target: 246 genes implicated in myeloma or cancer in general in a mixed gene discovery/confirmation effort; 2538 single nucleotide polymorphisms to detect amplifications and deletions at the single-gene and chromosome level; the IGH locus to detect translocations. We sequenced unmatched DNA from CD138-purified plasma cells from 418 patients with multiple myeloma at diagnosis, with a median follow-up of 5.3 years. We sequenced at an average depth of 337x using Hiseq2000 machines (Illumina Inc.). We applied algorithms developed in-house to call genomic events, filtering out potential artifacts and germline variants. We then ranker each event on its likelihood of being “oncogenic” based on clustering, recurrence and cross-reference with the COSMIC database.
Results
We identified 2270 gene mutations in 412/418 patients, and of those 688 were oncogenic. 342 patients harbored at least one oncogenic mutation. 215/246 genes showed at lease one likely somatic mutation, but only 106 showed at least one oncogenic mutation. 63% of oncogenic mutations were accounted for by the top 9 driver genes previously identified (KRAS, NRAS, TP53, FAM46C, BRAF, DIS3, TRAF3, SP140, IRF4), implying our gene discovery effort did not identify novel mutated genes. We included deletion of tumor suppressors, amplification of oncogenes, chromosomal copy number changes and IGH translocations for a total of 76 variables, so that 413/418 patients showed at least one informative driver genomic event, (median 4/patient). We investigated pairwise associations between events and found significant correlations, such as TP53 mutations and del(17p), CYLD mutations and del(16), FAM46C mutations and del(1p), SF3B1 mutations and t(11;14). Hotspots mutations of IRF4 lysine p.123 showed an inverse correlation with a hyperdiploid karyotype and del(16) as opposed to other missense mutations scattered along the gene, which has pathogenic implications.Survival was negatively affected by the cumulative burden of lesions in an almost linear fashion, with median survival of 10.97 and 4.07 years in patients with <=2 or >=7 lesions respectively, and this was independent of the nature of the genomic events. Given the heterogeneity and complex interplay of the variables we fitted a cox-proportional hazard model to predict survival. We found that mutations in TP53, amplifications of MYC, deletions of CYLD, amp(1q), del12p13.31 and del17p13 where the only significant events, all promoting shorter survival. In particular, TP53 mutations and deletions, often co-occurring, had an additive effect so that carriers of both showed a dismal survival of 17 months.
Conclusion
Due to the complex genomic landscape in MM, a discovery effort still requires large studies to derive significant associations. We conclude that a targeted sequencing approach may provide prognostic models and give insights into myeloma biology.
Session topic: New biological markers in MM
Keyword(s): Cytogenetic abnormalities, Mutation analysis, Myeloma, Prognosis
Type: Oral Presentation
Presentation during EHA21: On Saturday, June 11, 2016 from 11:30 - 11:45
Location: Auditorium 2
Background
Next-generation sequencing (NGS) studies have shown that multiple myeloma is a heterogeneous disease with a complex subclonal architecture and few recurrently mutated genes. The analysis of smaller regions of interest in the genome (“targeted studies”) allows interrogation of recurrent genomic events with reduces complexity of downstream analysis at a lower price.
Aims
Here, we performed the largest targeted study to date in multiple myeloma to analyze gene mutations, deletions and amplifications, chromosomal copy number changes and immunoglobulin heavy chain locus (IGH) translocations and correlate results with biological and clinical features.
Methods
We used Agilent SureSelect cRNA pull down baits to target: 246 genes implicated in myeloma or cancer in general in a mixed gene discovery/confirmation effort; 2538 single nucleotide polymorphisms to detect amplifications and deletions at the single-gene and chromosome level; the IGH locus to detect translocations. We sequenced unmatched DNA from CD138-purified plasma cells from 418 patients with multiple myeloma at diagnosis, with a median follow-up of 5.3 years. We sequenced at an average depth of 337x using Hiseq2000 machines (Illumina Inc.). We applied algorithms developed in-house to call genomic events, filtering out potential artifacts and germline variants. We then ranker each event on its likelihood of being “oncogenic” based on clustering, recurrence and cross-reference with the COSMIC database.
Results
We identified 2270 gene mutations in 412/418 patients, and of those 688 were oncogenic. 342 patients harbored at least one oncogenic mutation. 215/246 genes showed at lease one likely somatic mutation, but only 106 showed at least one oncogenic mutation. 63% of oncogenic mutations were accounted for by the top 9 driver genes previously identified (KRAS, NRAS, TP53, FAM46C, BRAF, DIS3, TRAF3, SP140, IRF4), implying our gene discovery effort did not identify novel mutated genes. We included deletion of tumor suppressors, amplification of oncogenes, chromosomal copy number changes and IGH translocations for a total of 76 variables, so that 413/418 patients showed at least one informative driver genomic event, (median 4/patient). We investigated pairwise associations between events and found significant correlations, such as TP53 mutations and del(17p), CYLD mutations and del(16), FAM46C mutations and del(1p), SF3B1 mutations and t(11;14). Hotspots mutations of IRF4 lysine p.123 showed an inverse correlation with a hyperdiploid karyotype and del(16) as opposed to other missense mutations scattered along the gene, which has pathogenic implications.Survival was negatively affected by the cumulative burden of lesions in an almost linear fashion, with median survival of 10.97 and 4.07 years in patients with <=2 or >=7 lesions respectively, and this was independent of the nature of the genomic events. Given the heterogeneity and complex interplay of the variables we fitted a cox-proportional hazard model to predict survival. We found that mutations in TP53, amplifications of MYC, deletions of CYLD, amp(1q), del12p13.31 and del17p13 where the only significant events, all promoting shorter survival. In particular, TP53 mutations and deletions, often co-occurring, had an additive effect so that carriers of both showed a dismal survival of 17 months.
Conclusion
Due to the complex genomic landscape in MM, a discovery effort still requires large studies to derive significant associations. We conclude that a targeted sequencing approach may provide prognostic models and give insights into myeloma biology.
Session topic: New biological markers in MM
Keyword(s): Cytogenetic abnormalities, Mutation analysis, Myeloma, Prognosis
Abstract: S447
Type: Oral Presentation
Presentation during EHA21: On Saturday, June 11, 2016 from 11:30 - 11:45
Location: Auditorium 2
Background
Next-generation sequencing (NGS) studies have shown that multiple myeloma is a heterogeneous disease with a complex subclonal architecture and few recurrently mutated genes. The analysis of smaller regions of interest in the genome (“targeted studies”) allows interrogation of recurrent genomic events with reduces complexity of downstream analysis at a lower price.
Aims
Here, we performed the largest targeted study to date in multiple myeloma to analyze gene mutations, deletions and amplifications, chromosomal copy number changes and immunoglobulin heavy chain locus (IGH) translocations and correlate results with biological and clinical features.
Methods
We used Agilent SureSelect cRNA pull down baits to target: 246 genes implicated in myeloma or cancer in general in a mixed gene discovery/confirmation effort; 2538 single nucleotide polymorphisms to detect amplifications and deletions at the single-gene and chromosome level; the IGH locus to detect translocations. We sequenced unmatched DNA from CD138-purified plasma cells from 418 patients with multiple myeloma at diagnosis, with a median follow-up of 5.3 years. We sequenced at an average depth of 337x using Hiseq2000 machines (Illumina Inc.). We applied algorithms developed in-house to call genomic events, filtering out potential artifacts and germline variants. We then ranker each event on its likelihood of being “oncogenic” based on clustering, recurrence and cross-reference with the COSMIC database.
Results
We identified 2270 gene mutations in 412/418 patients, and of those 688 were oncogenic. 342 patients harbored at least one oncogenic mutation. 215/246 genes showed at lease one likely somatic mutation, but only 106 showed at least one oncogenic mutation. 63% of oncogenic mutations were accounted for by the top 9 driver genes previously identified (KRAS, NRAS, TP53, FAM46C, BRAF, DIS3, TRAF3, SP140, IRF4), implying our gene discovery effort did not identify novel mutated genes. We included deletion of tumor suppressors, amplification of oncogenes, chromosomal copy number changes and IGH translocations for a total of 76 variables, so that 413/418 patients showed at least one informative driver genomic event, (median 4/patient). We investigated pairwise associations between events and found significant correlations, such as TP53 mutations and del(17p), CYLD mutations and del(16), FAM46C mutations and del(1p), SF3B1 mutations and t(11;14). Hotspots mutations of IRF4 lysine p.123 showed an inverse correlation with a hyperdiploid karyotype and del(16) as opposed to other missense mutations scattered along the gene, which has pathogenic implications.Survival was negatively affected by the cumulative burden of lesions in an almost linear fashion, with median survival of 10.97 and 4.07 years in patients with <=2 or >=7 lesions respectively, and this was independent of the nature of the genomic events. Given the heterogeneity and complex interplay of the variables we fitted a cox-proportional hazard model to predict survival. We found that mutations in TP53, amplifications of MYC, deletions of CYLD, amp(1q), del12p13.31 and del17p13 where the only significant events, all promoting shorter survival. In particular, TP53 mutations and deletions, often co-occurring, had an additive effect so that carriers of both showed a dismal survival of 17 months.
Conclusion
Due to the complex genomic landscape in MM, a discovery effort still requires large studies to derive significant associations. We conclude that a targeted sequencing approach may provide prognostic models and give insights into myeloma biology.
Session topic: New biological markers in MM
Keyword(s): Cytogenetic abnormalities, Mutation analysis, Myeloma, Prognosis
Type: Oral Presentation
Presentation during EHA21: On Saturday, June 11, 2016 from 11:30 - 11:45
Location: Auditorium 2
Background
Next-generation sequencing (NGS) studies have shown that multiple myeloma is a heterogeneous disease with a complex subclonal architecture and few recurrently mutated genes. The analysis of smaller regions of interest in the genome (“targeted studies”) allows interrogation of recurrent genomic events with reduces complexity of downstream analysis at a lower price.
Aims
Here, we performed the largest targeted study to date in multiple myeloma to analyze gene mutations, deletions and amplifications, chromosomal copy number changes and immunoglobulin heavy chain locus (IGH) translocations and correlate results with biological and clinical features.
Methods
We used Agilent SureSelect cRNA pull down baits to target: 246 genes implicated in myeloma or cancer in general in a mixed gene discovery/confirmation effort; 2538 single nucleotide polymorphisms to detect amplifications and deletions at the single-gene and chromosome level; the IGH locus to detect translocations. We sequenced unmatched DNA from CD138-purified plasma cells from 418 patients with multiple myeloma at diagnosis, with a median follow-up of 5.3 years. We sequenced at an average depth of 337x using Hiseq2000 machines (Illumina Inc.). We applied algorithms developed in-house to call genomic events, filtering out potential artifacts and germline variants. We then ranker each event on its likelihood of being “oncogenic” based on clustering, recurrence and cross-reference with the COSMIC database.
Results
We identified 2270 gene mutations in 412/418 patients, and of those 688 were oncogenic. 342 patients harbored at least one oncogenic mutation. 215/246 genes showed at lease one likely somatic mutation, but only 106 showed at least one oncogenic mutation. 63% of oncogenic mutations were accounted for by the top 9 driver genes previously identified (KRAS, NRAS, TP53, FAM46C, BRAF, DIS3, TRAF3, SP140, IRF4), implying our gene discovery effort did not identify novel mutated genes. We included deletion of tumor suppressors, amplification of oncogenes, chromosomal copy number changes and IGH translocations for a total of 76 variables, so that 413/418 patients showed at least one informative driver genomic event, (median 4/patient). We investigated pairwise associations between events and found significant correlations, such as TP53 mutations and del(17p), CYLD mutations and del(16), FAM46C mutations and del(1p), SF3B1 mutations and t(11;14). Hotspots mutations of IRF4 lysine p.123 showed an inverse correlation with a hyperdiploid karyotype and del(16) as opposed to other missense mutations scattered along the gene, which has pathogenic implications.Survival was negatively affected by the cumulative burden of lesions in an almost linear fashion, with median survival of 10.97 and 4.07 years in patients with <=2 or >=7 lesions respectively, and this was independent of the nature of the genomic events. Given the heterogeneity and complex interplay of the variables we fitted a cox-proportional hazard model to predict survival. We found that mutations in TP53, amplifications of MYC, deletions of CYLD, amp(1q), del12p13.31 and del17p13 where the only significant events, all promoting shorter survival. In particular, TP53 mutations and deletions, often co-occurring, had an additive effect so that carriers of both showed a dismal survival of 17 months.
Conclusion
Due to the complex genomic landscape in MM, a discovery effort still requires large studies to derive significant associations. We conclude that a targeted sequencing approach may provide prognostic models and give insights into myeloma biology.
Session topic: New biological markers in MM
Keyword(s): Cytogenetic abnormalities, Mutation analysis, Myeloma, Prognosis
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