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Purpose:Recurrent internal tandem duplication (ITD) mutations are observed in various cancers including acute myeloid leukemia (AML), where ITD mutations in tyrosine kinase receptor FLT3 are associated with poor prognostic outcomes. Several FLT3 inhibitors (FLT3i) are in clinical trials for high-risk FLT3-ITD–positive AML. However, the variability of survival following FLT3i treatment suggests that the mere presence of FLT3-ITD mutations might not guarantee effective clinical response. Motivated by the heterogeneity of FLT3-ITD mutations, we investigated the effects of FLT3-ITD structural features on the response of AML patients to treatment.Experimental Design: We developed the HeatITup (HEAT diffusion for Internal Tandem dUPlication) algorithm to identify and quantitate ITD structural features including nucleotide composition. Using HeatITup, we studied the impact of ITD structural features on the clinical response to FLT3i and induction chemotherapy in FLT3-ITD–positive AML patients.Results:HeatITup accurately identifies and classifies ITDs into newly defined categories of “typical” or “atypical” based on their nucleotide composition. A typical ITD's insert sequence completely matches the wild-type FLT3, whereas an atypical ITD's insert contains nucleotides exogenous to the wild-type FLT3. Our analysis shows marked divergence between typical and atypical ITD mutation features. Furthermore, our data suggest that AML patients carrying typical FLT3-ITDs benefited significantly more from both FLT3i and induction chemotherapy treatments than patients with atypical FLT3-ITDs.Conclusions:These results underscore the importance of structural discernment of complex somatic mutations such as ITDs in progressing toward personalized treatment of AML patients, and enable researchers and clinicians to unravel ITD complexity using the provided software.See related commentary by Gallipoli and Huntly, p. 460

Figure S1: Characterization of FLT3-ITD clones in the FLT3i cohort. Table S1: Confusion matrix of HeatITup and genetic reviewers manual annotation for sequences in Figure 3. Table S2: Univariate Cox regression analyses for the FLT3-ITD-positive UPENN cohort. Table S3: Cox regression analysis of FLT3-ITD duplication length for the non-FLT3i-treated cohort. Table S4: Cox regression analysis of FLT3-ITD classification for the non-FLT3i-treated cohort. Table S5: Cox regression analysis of FLT3-ITD duplication length with classification for the non-FLT3i-treated cohort. Table S6: Cox regression analysis of FLT3-ITD classification for the top third longest ITD duplications in the non-FLT3i-treated cohort (Benjamini-Hochberg adjusted p-values from long non-FLT3i-treated cohort analyses). Table S7: Cox regression analysis of FLT3-ITD spacer sequence exogenous fraction for the non-FLT3i-treated cohort. Table S8: Cox regression analysis of FLT3-ITD spacer sequence exogenous fraction for the top third longest ITD duplications in the non-FLT3i-treated cohort. Table S9: Cox regression analysis of FLT3i treatment for the UPENN cohort. Table S10: Cox regression analysis of FLT3-ITD duplication length for the FLT3i-treated cohort (Benjamini-Hochberg adjusted p-values from FLT3i cohort analyses). Table S11: Cox regression analysis of FLT3-ITD classification for the FLT3i-treated cohort (Benjamini-Hochberg adjusted p-values from FLT3i cohort analyses). Table S12: Cox regression analysis of FLT3-ITD spacer sequence exogenous fraction for the FLT3i-treated cohort.

Purpose: Recurrent internal tandem duplication (ITD) mutations are observed in various cancers including acute myeloid leukemia (AML), where ITD mutations in tyrosine kinase receptor FLT3 are associated with poor prognostic outcomes. Several FLT3 inhibitors (FLT3i) are in clinical trials for high-risk FLT3-ITD–positive AML. However, the variability of survival following FLT3i treatment suggests that the mere presence of FLT3-ITD mutations might not guarantee effective clinical response. Motivated by the heterogeneity of FLT3-ITD mutations, we investigated the effects of FLT3-ITD structural features on the response of AML patients to treatment. Experimental Design: We developed the HeatITup (HEAT diffusion for Internal Tandem dUPlication) algorithm to identify and quantitate ITD structural features including nucleotide composition. Using HeatITup, we studied the impact of ITD structural features on the clinical response to FLT3i and induction chemotherapy in FLT3-ITD–positive AML patients. Results: HeatITup accurately identifies and classifies ITDs into newly defined categories of “typical” or “atypical” based on their nucleotide composition. A typical ITD's insert sequence completely matches the wild-type FLT3, whereas an atypical ITD's insert contains nucleotides exogenous to the wild-type FLT3. Our analysis shows marked divergence between typical and atypical ITD mutation features. Furthermore, our data suggest that AML patients carrying typical FLT3-ITDs benefited significantly more from both FLT3i and induction chemotherapy treatments than patients with atypical FLT3-ITDs. Conclusions: These results underscore the importance of structural discernment of complex somatic mutations such as ITDs in progressing toward personalized treatment of AML patients, and enable researchers and clinicians to unravel ITD complexity using the provided software. See related commentary by Gallipoli and Huntly, p. 460