Unsupervised analysis reveals two molecular subgroups of serous ovarian cancer with distinct gene expression profiles and survival

Abstract

did not derive from high-versus low-grade serous carcinomas and were unrelated to histological (ovarian vs. fallopian) origin. Interestingly, there was considerable overlap between identified prognostic signature and a recently described invasion-associated signature related to stromal desmoplastic reaction. Several genes from this signature were validated by quantitative PCR; two of them-DSPG3 and LOX-were validated both in the initial and independent sets of samples and were significantly associated with OS and disease-free survival. Conclusions We distinguished two molecular subgroups of serous ovarian cancers characterized by distinct OS. Among differentially expressed genes, some may potentially be used as prognostic markers. In our opinion, unsupervised methods of microarray data analysis are more effective than supervised methods in identifying intrinsic, biologically sound sources of variability. Moreover, as histological type of the tumor is the greatest source of variability in ovarian cancer and may interfere with analyses of other features, it seems reasonable to use histologically homogeneous groups of tumors in microarray experiments.

Genes associated with bowel metastases in ovarian cancer

“…Fifteen of the 21 DEGs in BMets are ECM-related genes (Table S8). Whereas 13 of the 21 genes are reportedly expressed exclusively in the stroma [5,[21][22][23][24][25][26][27][28][29][30][31][32], we have determined that LRRC15 is expressed in both the stroma and the epithelial compartment ( Fig. 3).…”

“…This may suggest that BMet-upregulated genes are more immediately associated with surgical outcomes and intra-abdominal extension of cancer, whereas survival associations are most likely mediated by surgical results (RD0 vs non-RD0). Interestingly, Lisowska et al [24], reported EPYC (DSPG3) as 1 of 2 genes (along with LOX) significantly associated with overall survival and disease-free survival in OC.…”

Increased expression of UBE2T predicting poor survival of ovarian cancer: based on comprehensive analysis of UBE2s, clinical samples and the GEO database

“…GSE63885, based on the GPL570 platform (HG-U133_Plus_2; Affymetrix Human Genome U133 Plus 2.0 Array), contained 70 serous and 5 nonserous OC samples with complete clinical data [20]. All gene expression data were subjected to log2 transformation.…”

Proline-rich Protein 11 Overexpression is Associated With a More Aggressive Phenotype and Poor Overall Survival in Ovarian Cancer Patients

“…Importantly, due to the lack of speci c symptoms, the majority of OC patients often go undetected until the tumor has spread into the pelvic cavity or has invaded adjacent organs with nearly 60% of patients being diagnosed at advanced clinic stages since their rst doctor visit [2]. The clinicopathological features of OC that are correlated with a poor prognosis, include advanced stage, incomplete surgery, residual volume after surgery, and tumor histological type [3][4][5]. Despite the new emerging strategies targeting OC, recurrence still remains the most critical threat to the long-term survival of OC patients.…”