Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis

Abstract

Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients have an excellent response to therapy, while others have a poor response? We studied gene expression in whole blood samples from 112 patients from a large phase III randomized trial (clinicaltrials gov. Identifier: NCT00471497), dichotomizing cases into good responders (BCR::ABL1 ≤10% on the International Scale by 3 and 6 months and ≤0.1% by 12 months) and poor responders (failure to meet these criteria). Predictive models based on gene expression demonstrated the best performance (area under the curve =0.76, standard deviation =0.07). All of the top 20 pathways overexpressed in good responders involved immune regulation, a finding validated in an independent data set. This study emphasizes the importance of pretreatment adaptive immune response in treatment efficacy and suggests biological pathways that can be targeted to improve response.

Figure 1.

Early differences in patient tyrosine kinase inhibitor response persisted up to 10 years. BCR::ABL1^IS (log₁₀ scale) over time for good (blue) and poor (red) responders. IS: International Scale. Calculations of BCR::ABL1^IS levels >10% are less accurate than those ≤10%.

Figure 2.

Multivariate analysis of clinical variables vs responder status.

Figure 3.

Genes upregulated in good and poor responders. Genes listed are those that were found in over 10% of the gene expression models (see Methods). The top upregulated genes in the good responder group were enriched in genes associated with immunity, in agreement with the immune pathway enrichment in good-responders (below, Figure 4).

Figure 4.

Figure 4. Immune-related pathways were enriched in good responders. (A) Normalized enrichment score (NES) and associated P value of 3,478 gene ontology gene sets. Immune-related gene sets are indicated in blue. Other gene ontology gene sets are in red. Positive NES indicates positive association with good response. (B) P values of the 20 most significantly dysregulated gene sets; all are immune-related.

Figure 5.

Cytotoxic lymphocytes were enriched in responders. Comparison of immune cell infiltration (inferred by MCP-counter) in the ENESTnd and Branford data sets. NK: natural killer.