A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia

Round 1

Reviewer 1 Report

Very accurate research on intriguing topics such as the metabolomic comprehension of leukemic drug resistance and identification of biomarkers of prognosis candidate to target therapies. It gives a valuable background for future investigation and overcoming of multidrug resistance 

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Reviewer 2 Report

The role of metabolic changes in acute myeloid leukemia and  their role in leukemogenesis has been recently highlighted.

In the present paper the authors focused on fatty acid metabolism, investigating its potential impact on prognosis and on response to therapy.

They developed a risk score starting from the different expression of genes involved in fatty acid metabolism and identified two AML groups with different prognosis, drug sensitivity, microenvironmental alterations.

The paper is interesting and contains many new and useful information, and adds knowledge on the very complex leukemia pathogenesis. Methods are clear, and so figures, references updated.

There are only few points needing to be clarified.

1.     They found and association between score risk and molecular risk: according to ELN?, recent WHO classification? There are many differences among the different molecular risk scores

2.     They observed significant differences in TME according to the FAM risk score: could the cytokine level or the expression of checkpoint inhibitors be used to indirect marker of high score?

3.     They tested drug sensitivity in the two different groups, demonstrating higher sensitivity to cytarabine in the low risk group. How about sensitivity to anthracyclines?

4.     PPI analysis identified CD163 as the most relevant prognostic factor, suggesting that it could be a novel therapeutic target in AML.  CD163 is considered a biomarker of macrophage activation and of disease progression. In the paper is not clear if expression of CD163 in increased on macrophages or on leukemia cells? Did they observed different expression according to lineage origin of blast cells?

5.     How can these new information practically used in the clinical practice? 

Author Response

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Reviewer 3 Report

In this work `A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia‘ by Wang et al the authors have performed a through bioinformatic study with the clinical data from available online resources and proposed a novel prognostic signature based on  fatty acid metabolism associated genes for patients with AML. The study is decently designed, methods are adequately described. Necessary figures and illustrations are included to support the data. The study has a limitation of being only based on bioinformatic analysis  without any experimental validation. However, this work provides a basis for further investigation into the field of fatty acid metabolism in AML.

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Round 2

Reviewer 2 Report

I read the modified paper.

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