Here, we analyzed USC datasets from TCGA and GTEx and uncovered 1385 genes that are dysregulated USC tissues relative to normal endometrial tissue. KEGG pathway analysis revealed that these genes mainly belong to cancer-associated pathways, including melanoma and bladder cancer as well as in pathways associated with cell adhesion, cell cycle, PI3K-Akt signaling pathway, cancer-linked microRNAs and transcriptional misregulation. Disruption of cell adhesion may explain why USC tends to disseminate early, spreading to fallopian tubes or invading lymph-vascular space. The tumor suppressor, TP53 is the frequently mutated gene in USC (34). USC’s high proliferative rate dysregulated cycle control may contribute to the high relapse and mortality rates in endometrial cancers. The PI3K/AKT/mTOR signaling pathway is the most frequently dysregulated pathway in EEC (34). In USC, PIK3CA mutation occurs in about 30% of cases (11, 34–35), which is consistent with the involvement of the PI3K-Akt signaling pathway seen from our analysis. Inhibition of PI3K/AKT/mTOR signaling strongly suppresses EEC progression (36–38) and clinical trials targeting PI3K/AKT/mTOR signaling in solid tumors have shown promise (39). However, the benefits of this against in endometrial cancers is controversial due to the complexity of pharmacological action and toxicity (40). Further studies are needed to better target PI3K/AKT/mTOR signaling in endometrial cancer.
The TGCA database, which offers a collection of complete transcriptomic data and associated clinical information, is publicly available for data mining (41). To identify important dysregulated genes associated with USC outcomes, we used LASSO and Cox regression analysis. LASSO is widely applied in modeling high-dimensional data and avoids overfitting risk and improves prediction accuracy (42). Our analysis generated a 4-gene signature for predicting USC OS by calculating each patient’s risk score. We find that patients with high scores exhibit poor outcomes relative to those with low scores, an observation that was validated in both the training and testing sets. ROC curve analysis revealed this signature’s superiority over conventional prognostic parameters (age, myometrium invasion, node metastasis, and stage) in the training and testing sets. Our data show that both the 4-gene signature and disease stage are independent prognostic indicators OS. Patients with late-stage of the disease have an unfavorable prognosis for most malignant solid tumors. However, for USC, the early-stage disease does not necessarily correlate with good prognosis due to the tumor’s propensity for shedding, spreading and invading the lymph-vascular space even when the lesion confined to the endometrium or polyps. Management of patients with early stage USC is controversial (4, 43–44). Our signature identified high-risk patients in the early stage USC group who had much poorer OS relative to low-risk patients in the same group. Our data show that this signature performed better in the early stage group than in the late stage group, highlighting its potential value in guiding the management for early stage USC.
The average recurrence rate for stage IA USC after chemotherapy, radiotherapy or surgery is 8.7%, 25% and 12.4% respectively. For stage IB/IC the corresponding recurrence rate are 10.8%, 36.6% and 37.3%, respectively (11). Our 4-gene signature predicts a higher recurrence risk in the high-risk group relative to the low-risk group. Consistently with our OS, ROC curve analysis, this 4-gene signature exhibited superior effectiveness over conventional indicators of RFS. Both the signature and disease stage were an independent prognostic factor for RFS. Our data show that the 4-gene signature is effective at RFS prediction in late stage disease but showed no difference between high and low-risk groups in early stage. This may be due to too few recurrent cases (8 cases out of 45 cases) in early stage in the TCGA cohort.
The 4 genes in the signature have been associated with various cancers. KRT23 has been implicated as an oncogene in liver cancer (46) and colorectal cancer (47). CXCL1 is overexpressed in EEC tissue relative to normal endometrium and promotes tumorigenesis by promoting neutrophil chemotaxis (48). Snail induces ovarian epithelial-mesenchymal transition via CXCL1 and CXCL2, representing an immunological therapeutic target (49). SOX9 overexpression in uterine epithelium may induce endometrial hyperplastic lesions (50), promoting endometrial cancer cell proliferation (51). ABCA10 has been proposed as a prognostic marker in ovarian carcinoma (52). Germline single nucleotide polymorphisms in ABCA10 may affect follicular lymphoma overall survival (53). So far, none of the 4 genes has been associated with USC, though CXCL1 and SOX9 are associated with EEC progression.