45P - Integrative analysis of TCGA DNA methylation, RNA-sequencing, and variant dataset using machine learning in predicting endometrial cancer recurrence

Background

Although 4 molecular subtypes of endometrial cancer (EC) by The Cancer Genome Atlas (TGGA) have distinctive prognostic features, prognosis within each subtype could vary depending on histological and molecular factors. By merging omics datasets and machine learning analyses, we attempted to identify biomarkers related to the recurrence within each molecular subtype.

Methods

From TCGA multi-omics datasets, 116 EC samples with DNA methylation, RNA-seq, and common variants as well as recurrence data were used for analysis. Differentially expressed genes (DEGs) and differentially methylated regions (DMRs) were retrieved by t-test between the recurrence and non-recurrence groups. DEGs and DMRs were visualized using volcano plots and heat maps. The machine learning approaches, namely decision tree (DT) and random forest (RF) models, were used to find the molecular factors to best discriminate the following 4 groups: copy number-high (CN-H) with recurrence, CN-H without recurrence, copy number-low (CN-L) with recurrence, and CN-L without recurrence. Critical gene expressions or DNA methylation levels in each molecular subtypes were presented as a boxplot.

Results

Three omics datasets were merged with 378,278 CpG sites, 53,409 normalized gene expression levels, 118,555 genomic region variants, and 18,603 gene variants. Through DT and RF, PARD6G-AS1, CSMD1, TESC, and CD44 were selected. Boxplot revealed that hypomethylation of PARD6G-AS1, hypermethylation of CSMD1, and increased TESC expression were significantly associated with increased risk of recurrence in the CN-H group. Also, overexpression of CD44 was significantly associated with recurrence in the CN-L group. After validation of these 4 parameters using TCGA raw data, PARD6G-AS1 and CD44 remained their statistical significance (P=0.006 and 0.020, respectively). Hypomethylation of PARD6G-AS1 in CN-H and CD44 overexpression in CN-L demonstrated significant association with both advanced stage and lymph node metastasis.

Conclusions

Hypomethylation of PARD6G-AS1 in CN-H and CD44 overexpression in CN-L could be predictive markers in endometrial cancer recurrence.

Editorial acknowledgement

Clinical trial identification

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.