Analysis of prognostic biomarker models and immune microenvironment in acute myeloid leukemia by integrative bioinformatics

Wang, Naihong

doi:10.1007/s00432-023-04871-3

Cited by 5 publications

(1 citation statement)

References 35 publications

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“…The study of Liu et al demonstrated that high miR-107 or miR-17 expression levels were associated with poorer overall survival and event-free survival in the chemotherapy cohort of patients with de novo AML [ 48 ]. A special place is occupied by immunity-associated biomarkers, such as immune-related long noncoding RNAs [ 49 ] and immune microenvironment genes [ 50 ], which are closely related to resistance to immunotherapy and poor prognosis for AML patients. Such molecular and genetic features are designed to complement the risk stratification by genetics and represent high-tech approaches with high cost and the need for specially trained staff.…”

Section: Discussionmentioning

confidence: 99%

Effective Prognostic Model for Therapy Response Prediction in Acute Myeloid Leukemia Patients

Kolesnikova¹,

Sen’kova

Поспелова

et al. 2023

JPM

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Acute myeloid leukemia (AML) is a hematopoietic disorder characterized by the malignant transformation of bone marrow-derived myeloid progenitor cells with extremely short survival. To select the optimal treatment options and predict the response to therapy, the stratification of AML patients into risk groups based on genetic factors along with clinical characteristics is carried out. Despite this thorough approach, the therapy response and disease outcome for a particular patient with AML depends on several patient- and tumor-associated factors. Among these, tumor cell resistance to chemotherapeutic agents represents one of the main obstacles for improving survival outcomes in AML patients. In our study, a new prognostic scale for the risk stratification of AML patients based on the detection of the sensitivity or resistance of tumor cells to chemotherapeutic drugs in vitro as well as MDR1 mRNA/P-glycoprotein expression, tumor origin (primary or secondary), cytogenetic abnormalities, and aberrant immunophenotype was developed. This study included 53 patients diagnosed with AML. Patients who received intensive or non-intensive induction therapy were analyzed separately. Using correlation, ROC, and Cox regression analyses, we show that the risk stratification of AML patients in accordance with the developed prognostic scale correlates well with the response to therapy and represents an independent predictive factor for the overall survival of patients with newly diagnosed AML.

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Section: Discussionmentioning

confidence: 99%