Identifying key genes and functionally enriched pathways in acute myeloid leukemia by weighted gene co-expression...

Area of Science:

• Hematology
• Genomics
• Molecular Biology

Background:

• Acute myeloid leukemia (AML) is a heterogeneous cancer with incomplete understanding of prognostic biomarkers.
• Advancements in sequencing technology necessitate the identification of reliable biomarkers for AML prognosis.

Purpose of the Study:

• To identify novel gene expression biomarkers for predicting the prognosis of acute myeloid leukemia (AML).
• To explore potential driver genes and molecular signatures for AML patient survival.

Main Methods:

• Weighted Gene Co-expression Network Analysis (WGCNA) was applied to analyze gene mutation expression, methylation levels, and mRNA expression in 103 AML samples.
• A total of 6153 genes were screened, leading to the identification of seven co-expression modules and twelve potential prognostic biomarkers.

Main Results:

• Twelve biomarkers were identified, enabling the classification of AML samples into two subgroups with significantly different prognoses.
• Seven differentially expressed genes (HOXB-AS3, HOXB3, SLC9C2, CPNE8, MEG8, S1PR5, MIR196B) were highlighted, involved in glucose metabolism, glutathione biosynthesis, and signaling pathways.

Conclusions:

• The identified biomarkers and co-expression modules offer potential molecular signatures for predicting AML patient survival.
• These findings may guide future experiments for identifying clinical drug targets and improving AML treatment strategies.