Lian Li

Identification of DNA methylation based prognostic subtype and signature in epithelial ovarian cancer

DNA methylation plays a crucial role in the development and progression of cancer and has been utilized for subtyping various tumors. This study focused on classifying epithelial ovarian cancer (EOC) based on DNA methylation and characterizing the subtypes through an integrated analysis of genomic, transcriptomic, and clinical data. We performed genome-wide DNA methylation profiling on 137 EOC tumor tissues using Infinium MethylationEPIC array and four methylation subtypes (MS1-MS4) were identified by non-negative matrix factorization (NMF) approach, showing significant differences in prognosis (P = 2.413 × 10⁻⁹). The MS1 group showed the best prognosis and the most favorable response to paclitaxel in combination with platinum-based chemotherapy. MS2 exhibited a gene expression pattern of relatively high immune cell infiltration and MS3 had a gene expression pattern associated with metabolic related pathway with a moderate prognosis. In contrast, MS4 had the poorest prognosis and was marked by the highest methylation levels among the four subtypes. A four-differential methylation position (DMP) signature was constructed for prognosis prediction and nomogram was also developed for enhancing clinical utility. Together, this study identified a novel molecular subtype for EOC, elucidating the heterogeneity of EOC from an epigenetic perspective and providing a new strategy for personalized treatment options for EOC patients.

Targeted sequencing and functional interrogation identified novel variant at 12q14.2 associated with risk of ovarian cancer in Han Chinese women

Abstract Chromosome 12q14.2 has been reported as a potential risk locus for epithelial ovarian cancer (EOC) in genome-wide association study (GWAS). We performed targeted sequencing around the rs11175194 at chromosome 12q14.2 and identified five potential risk variants. The association between these five variants and EOC risk was evaluated in 893 EOC cases and 1292 controls. We identified that rs11175195 (P = 1.94 × 10−6, OR = 1.36, 95% CI = 1.20–1.54) was significantly associated with EOC risk in validation study and after meta-analysis with previous GWAS data, rs11175195 reached genome-wide significant level (P < 5 × 10−8). Functional annotation and expression quantitative trait loci analysis prioritized rs11175194 as a causal variant at this locus. The presence of G-rs11175194 risk allele increased binding affinity of the transcription factor NR1H4 and upregulate SRGAP1 gene expression. Overexpression of SRGAP1 promotes the proliferation and invasion in ovarian cancer cell lines. In conclusion, we identified a novel susceptibility locus of ovarian cancer and revealed a potential molecular mechanism for ovarian cancer carcinogenesis. These results may provide a potential biomarker and therapeutic target for ovarian cancer.