Integrated genome, transcriptome sequencing identifies subtypes of AML, myelodysplastic syndrome
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ORLANDO — The integration of transcriptomic and genomic sequencing data from a large cohort of adults with acute myeloid leukemia or myelodysplastic syndromes allowed for the identification of subtypes and constellations of driver mutations, according to study results presented at ASH Annual Meeting and Exposition.
The approach’s prognostic significance exceeded that of prior gene panel-based classification schema, Ilaria Iacobucci, PhD, staff scientist at St. Jude Children’s Research Hospital, and colleagues concluded.
AML and myelodysplastic syndrome (MDS) are a heterogenous group of diseases characterized by clonal explanation of undifferentiated myeloid precursors, impaired hematopoiesis and bone marrow failure. Differences in blast threshold distinguish AML ( 20%) from MDS syndrome (< 20%).
“In the past decade, intensive sequencing efforts have dramatically improved our understanding of these diseases, with identification of key driver mutations that contribute either to the pathogenesis or outcomes of AML and MDS,” Iacobucci said during a press conference. “However, most of these studies have focused on targeted DNA sequencing-based approaches or have been limited to the analysis of specific homogenous subtypes of leukemia.”
This has limited the identification of novel mutational patterns and gene expression clusters, Iacobucci said.
Researchers hypothesized that integrating genomic analysis — including genetic mutations, gene expression and structural genetic changes — may reveal important insights into leukemia classification and outcomes.
They aimed to perform an unbiased analysis of AML and MDS, using genomic and transcriptome data and clinicopathologic features and clinical outcome to define myeloid leukemia subtypes of diagnostic, prognostic and therapeutic relevance. The study was part of the 5K Project conducted at Munich Leukemia Laboratory, which to date has analyzed approximately 5,000 cases from 30 hematologic entities by whole-genome and transcriptome sequencing.
Iacobucci and colleagues performed an integrated genome-wide mutational/transcriptomic analysis of samples from a large cohort of 1,304 adults with AML (n = 598; median age, 68 years; range, 17.8-93.1) or MDS (n = 706; median age, 73.2 years; range, 23.3-93.1) to accurately define subtypes that could be relevant for diagnosis, prognosis or therapeutic development.
Investigators identified more than 7,000 variants in 839 genes — 33% of which were potential driver genes — with a median five (range, 1-18) mutations per case.
The most frequently mutated genes were TET2 — which occurred more frequently in MDS than AML (P = .0011) — and DNMT3A, which occurred more frequently in AML than MDS (P < .0001).
Researchers determined some mutations could be shared between AML and MDS; however, the frequency varied depending on the specific subtype.
For example, 13% of all cases included NPM1 mutations (27% for AML vs. 0.8% for MDS).
However, if NPM1 is combined with additional mutations, the outcome may vary. The combination of NPM1 and cohesion mutations conferred better outcomes than NPM1 alone, whereas the presence of both NPM1 and FLT3 mutations were associated with poorer outcomes (P = .0071).
Nine percent of AML and MDS cases had overexpression of meningioma 1 (MN1), a transcriptional coactivator that cooperates with the nuclear receptors for retinoic acid and vitamin D. Low MN1 expression was associated with better median survival than high expression (61.1 months vs. 21.2 months).
Researchers observed distinct gene expression profiles with overexpression of HOXA9 and MEIS1, as well as common mutually exclusive mutations in RUNX1 (29%) and TP53 (23%).
RUNX1 mutations — identified in 12.5% of AML cases and 9.5% of MDS cases — appeared associated with poor outcomes in both diseases.
TP53 mutations — present in 12% of AML cases and 10% of MDS cases — were associated with complex karyotype in both AML and MDS, as well as older age.
The genomic landscape of MDS cases were very complex, Iacobucci said.
“We were able, based on the combinations of different mutations and the gene expression, to define different subgroups and we confirmed the importance of complementary mutations to determine specific outcomes,” she said.
The study provides a richer understanding of disease subtypes, comparable to “a dictionary” of genomic alterations, Iacobucci said.
This information will help guide future research into how these diseases develop, as well as how new therapies can target them, according to researchers. In addition, the study demonstrated the feasibility of full-genome sequencing, as well as the value it provides for identifying disease subtypes and guiding prognosis.
“This is the sort of dataset that is going to prove invaluable to precision medicine efforts,” Iacobucci said. “As we have seen in lymphoid malignancies, the study shows the power of integrated genome and transcriptome sequencing to identify new disease subgroups of clinical significance not evident on conventional pathologic and molecular analysis.” – by Mark Leiser
Reference: Iacobucci I. Abstract LBA-4. Presented at: ASH Annual Meeting and Exposition; Dec. 7-10, 2019; Orlando.
Disclosures: Iacobucci reports no relevant financial disclosures. Please see the abstract for all other authors’ relevant financial disclosures.