An IDO1-related immune gene signature predicts overall survival in acute myeloid leukemia.
Simone RagainiSarah WagnerGiovanni MarconiSarah ParisiChiara SartorJacopo NanniGianluca CristianoAnnalisa TalamiMatteo OliviDarina OcadlikovaMarilena CiciarelloGiulia CorradiEmanuela OttavianiCristina PapayannidisStefania PaoliniJayakumar VadakekolathuMichele CavoSergio RutellaAntonio CurtiPublished in: Blood advances (2021)
The contribution of the bone marrow (BM) immune microenvironment (TME) to acute myeloid leukemia (AML) development is well-known, but its prognostic significance is still elusive. Indoleamine 2,3-dioxygenase 1 (IDO1), which is negatively regulated by the BIN1 proto-oncogene, is an interferon (IFN)-γ-inducible mediator of immune tolerance. With the aim to develop a prognostic IDO1-based immune gene signature, biological and clinical data of 732 patients with newly diagnosed, non-promyelocytic AML were retrieved from public datasets and analyzed using established computational pipelines. Targeted transcriptomic profiles of 24 diagnostic BM samples were analyzed using the NanoString's nCounter platform. BIN1 and IDO1 were inversely correlated and individually predicted overall survival. PLXNC1, a semaphorin receptor involved in inflammation and immune response, was the IDO1-interacting gene retaining the strongest prognostic value. The incorporation of PLXNC1 into the 2-gene IDO1-BIN1 score gave rise to a powerful immune gene signature predicting survival, especially in patients receiving chemotherapy. The top differentially expressed genes between IDO1low and IDO-1high and between PLXNC1low and PLXNC1 high cases further improved the prognostic value of IDO1 providing a 7 and 10-gene immune signature, highly predictive of survival and correlating with AML mutational status at diagnosis. Taken together, our data indicate that IDO1 is pivotal for the construction of an immune gene signature predictive of survival in AML patients. Given the emerging role of immunotherapies for AML, our findings support the incorporation of immune biomarkers into current AML classification and prognostication algorithms.
Keyphrases
- acute myeloid leukemia
- genome wide
- genome wide identification
- newly diagnosed
- copy number
- allogeneic hematopoietic stem cell transplantation
- bone marrow
- machine learning
- dendritic cells
- free survival
- healthcare
- deep learning
- stem cells
- squamous cell carcinoma
- oxidative stress
- emergency department
- artificial intelligence
- acute lymphoblastic leukemia
- genome wide analysis
- patient reported outcomes
- patient reported
- rectal cancer