Clonal hematopoiesis of indeterminate potential (CHIP) may play a greater role in hematologic malignancies than previously realized, according to a study published in Blood Advances. In addition to this finding, researchers also characterized the role of DTA mutations (i.e., mutations in DNMT3A, TET2, and ASXL1 genes) in hematologic neoplasms and defined mutation-driven entities. Researchers hope that these data may offer further therapeutic options for patients who otherwise have no specific treatment possibilities, according to lead study author Anna Stengel, PhD, of the Munich Leukemia Laboratory in Germany.
“The identification of certain mutations could, independently of the respective diagnosis, potentially be used therapeutically for so-called basket trials, a new type of clinical trial for which eligibility is based on the presence of a specific genomic alteration that is irrespective of histology,” Dr. Stengel added.
In the study, the researchers used a Germany-based real-world dataset to analyze mutational landscapes and their association with CHIP-related mutations and patient age (see FIGURE). The analysis included 122 genes in 3,096 cases of 28 hematologic malignancies, including myelodysplastic syndromes (MDS), chronic lymphocytic leukemia (CLL), acute myeloid leukemia (AML), and multiple myeloma, among several others.
FIGURE. Graphic Summary of Age-Associated Molecular Mutations. The circles include all mutations across all entities that were found to be associated with younger age (gray, left side) or older age (light red, right) or for which the age association was found to differ between entities (middle). Script size indicates the number of entities with changes in this mutation.
The circles include all mutations across all entities that were found to be associated with younger age (gray, left side) or older age (light red, right) or for which the age association was found to differ between entities (middle). Script size indicates the number of entities with changes in this mutation.
Several of the MDS/myeloproliferative neoplasm (MPN) overlap entities had the highest numbers of mutations in the 122 selected genes. These entities included the following:
- atypical chronic myeloid leukemia (aCML; range = 1-7 mutations)
- chronic myelomonocytic leukemia (CMML; range = 1-6 mutations)
- MDS/MPN, unclassifiable (MDS/MPN-U; range = 2-5 mutations)
- secondary AML cases (range = 2-8)
The disease entities that featured very high frequencies of mutations included the following:
- aCML (ASXL1; 86%)
- blastic plasmacytoid dendritic cell neoplasm (TET2; 67%)
- Burkitt lymphoma (TP53; 60%)
- CMML (TET2, 67%; ASXL1, 58%)
- follicular lymphoma (KMT2D, 87%; CREBBP, 73%)
- hairy cell leukemia (BRAF; 100%)
- lymphoplasmacytic lymphoma (LPL ; MYD88, 98%; CXCR4, 51%)
- MDS/MPN-U (ASXL1; 60%)
- MPN (JAK2; 68%)
- B-cell non-Hodgkin lymphoma (B-NHL ; TP53, 50%)
- T-cell non-Hodgkin lymphoma (T-NHL ; STAT3, 52%)
Dr. Stengel noted that some mutational patterns that occur very frequently in a certain entity could be used in differential diagnostics for assignment of a correct diagnosis, particularly in difficult cases, which would improve classification.
Patients who were age 60 or younger had a lower median number of mutations compared with patients who were older than 60 (one vs. two, respectively; p<0.001). The investigators found a significant association between age and the number of mutations per patient in the overall cohort (p<0.001), as well as for several disease entities: AML (p<0.001), B-cell acute lymphoblastic leukemia (p=0.015), CLL (p=0.039), MDS (p<0.001), MPN (p<0.001), and T-cell acute lymphoblastic leukemia (T-ALL; p<0.005).
Additionally, the investigators observed increased frequencies of mutations in EZH2, IDH2, RUNX1, SRSF2, and NRAS in cases with one or more DTA mutation. In contrast, TP53, KRAS, SF3B1, and WT1 were more frequent across disease entities in cases without DTA mutations.
Although mutations in TET2 and ASXL1 showed a very high frequency in certain entities in the study, these mutations, together with DNMT3A, were found to belong to the genes that depicted the broadest distribution across entities and were also detected with frequencies >5% in lymphoid malignancies comprising T-ALL, T-NHL, natural killer cell neoplasm, B-NHL, mantle cell lymphoma, LPL, and hairy cell leukemia variant.
“Thus, our data indicate that CHIP might play a greater role in a higher number of hematologic malignancies than so far anticipated,” Dr. Stengel said. “However, further studies analyzing samples and the [variant allele frequencies] of the respective mutations during several time points of the respective diseases are required to further elucidate this question.”
Any conflicts of interest declared by the authors can be found in the original article.
Stengel A, Baer C, Walter W, et al. Mutational patterns and their correlation to CHIP-related mutations and age in hematological malignancies. Blood Adv. 2021;5(21):4426-4434.