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Signature of 17 Genes Could Predict Prognosis in AML Patients

NEW YORK (GenomeWeb) – An international team of researchers has homed in on a 17-gene signature derived from leukemia stem cells to predict whether acute myeloid leukemia patients would respond to treatment.

The University of Toronto-led team of researchers examined differences in gene expression between leukemia stem cells and non-leukemia stem cells in samples obtained from 78 AML patients. As they reported in Nature today, the researchers whittled that set of differentially expressed genes down to 17. A high score based on this set of genes was linked to poor prognosis, the researchers reported, adding that scores could be used to identify patients who wouldn't benefit from standard treatment.

"We identified the minimal set of genes that were most critical for predicting survival in these other groups of AML patients, regardless of where they were treated," Toronto's Jean Wang said in a statement. "With this core 17-gene score, we have shown we can rapidly measure risk in newly diagnosed AML patients."

Wang and her colleagues sorted 83 cell samples from 78 AML patients and assessed those cell fractions' leukemia stem cell activity. By comparing gene expression among leukemia stem cells and non-leukemia stem cells, the researchers devised a list of more than 100 genes whose expression varied by more than 2-fold between the two cell types.

Using a dataset of 495 patients from the Gene Expression Omnibus database in which 89 of those 104 genes were captured, the researchers sought to edit that set of genes down to an optimal, core group. By applying a statistical regression algorithm based on the least absolute shrinkage and selection operator, they obtained a 17-gene signature they dubbed LSC17.

High LSC17 scores, as calculated through a weighted sum of the expression of the 17 genes, are associated with poor overall and event-free survival, the researchers reported. At diagnosis, patients with high scores also had higher percentage of bone marrow blasts, higher incidence of the FLT3 internal tandem duplication mutations, and adverse cytogenetics as well as a high relapse rate and lower response rate to chemotherapy.

The researchers confirmed this link between LSC17 scores and survival in three independent AML cohorts.

To develop this gene signature for clinical use, Wang and her colleagues incorporated it into a custom NanoString assay. They tested that assay on a set of 307 AML patients from the Princess Margaret Cancer Centre and found that here, too, a high LSC17 score was linked with adverse prognostic features and shorter overall survival, as well as with shorter event-free and progression-free survival, as compared to low scores.

The investigators noted that the score kept its prognostic value in a multivariate survival analysis even for the subset of AML patients who were cytogenetically normal. This, they said, shows that the score based on the NanoString assay has broad applicability and a strong prognostic value.

A high LSC17 score was also associated with poor outcomes among patients who'd undergone allogeneic stem cell transplantation (aSCT), the researchers reported, noting that because of its associated mortality risk, such treatment is typically restricted to patients deemed to be at a high risk of relapse. Because of this and other findings, they suggested that LSC17 scores could be used to help determine which patients should pursue aSCT treatment.

In addition, Wang and her colleagues found that, for the Princess Margaret cohort, the LSC17 score could also predict therapy resistance among newly diagnosed patients. They extended this using data from the ALFA-0701 trial to gemtuzumab ozogamicin (GO) response to report that patients with low LSC17 scores, but not high scores, benefitted from adding GO treatment to standard chemotherapy. The scores, they said, could be used to identify patients who'd benefit from such treatment.

"The LSC17 score is the most powerful predictive and prognostic biomarker currently available for AML, and is the first stem cell-based biomarker developed in this way for any human cancer," Wang said. "Clinicians will now have a tool that they can use upfront to tailor treatment to risk in AML."

On a more cautious note, however, Gerrit Schuurhuis from the Free University Medical Center in Amsterdam noted in a commentary that "[t]he clinical benefits of the LSC17 score must be assessed, because prognostic value does not always lead to a meaningful clinical advantage."

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