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Transcriptome-Wide Cox Regression Identifies Candidate Survival-Associated Genes in Newly Diagnosed Acute Myeloid
Songphol Tungjitviboonkun1, Nikhil Mullapudi1, Elly Gardev1
1Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA.
Cancer Informatics
|August 10, 2026
Summary
Researchers identified 46 genes linked to survival in acute myeloid leukemia (AML). Gene expression levels of markers like FAM213A and PJA2 may help predict patient outcomes in AML.
Area of Science:
- Hematology
- Genomics
- Cancer Biology
Background:
- Acute myeloid leukemia (AML) is characterized by significant biological diversity.
- Current prognostic systems do not fully encompass this heterogeneity.
- Identifying novel prognostic markers is crucial for refining AML risk stratification.
Purpose of the Study:
- To conduct a transcriptome-wide analysis to identify gene expression markers associated with overall survival in newly diagnosed AML patients.
- To discover potential biomarkers that can enhance existing prognostic frameworks for AML.
Main Methods:
- Utilized gene expression and clinical data from 399 newly diagnosed AML patients.
- Performed Cox proportional hazards regression for 22,836 genes to assess survival associations.
- Applied Bonferroni correction for multiple testing to ensure statistical rigor.
Main Results:
- Identified 46 genes significantly associated with overall survival in AML.
- Higher expression of FAM213A and TJP2 correlated with increased mortality risk.
- Elevated expression of PJA2, MICALL2, and LTK was linked to improved survival outcomes.
Conclusions:
- This study identified multiple genes associated with survival in newly diagnosed AML.
- These genes represent potential prognostic biomarkers to complement current AML risk stratification.
- Further validation in independent patient cohorts is recommended.
