Background Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study investigated the prognostic value of necroptosis-related genes (NRGs) and the immune landscape in OC. Methods The gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs) between OC and normal tissueswere identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB) and the drug sensitivity were also analyzed based on the two-NRG signature in OC. Results Totally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8, and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found to be more sensitive in the low-risk group. Conclusions MAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.
Background: Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study tried to investigate the prognostic value of necroptosis‐related genes (NRGs) and the immune landscape in OC. Methods: The gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs)were identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB)and the drug sensitivity were also analyzed based on the two-NRG signature in OC. Results: Totally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8 and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found more sensitive in the low-risk group. Conclusions: MAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.
Rationale: Endometrial stromal sarcoma (ESS) is a rare disease in patients with uterine malignancies, accounting for <1%. Low-grade endometrial stromal sarcoma (LGESS) accounts merely 0.2% of gynecologic malignant tumor. Primary low-grade extrauterine endometrioid stromal sarcomas (LGEESS) is even more uncommon, with only a few documented case reports. We report a case of primary LGEESS exhibiting widely invasion in multiple organs after hysterectomy, which is the first case reported in Jiangsu Province of China. Patient concerns: A 42-year-old nulliparous female with dysgnosia presented with a moderate amount of irregular vaginal bleeding, abdominal pain and distension, and frequent urination for 2 days. Her surgical history included a total hysterectomy and bilateral salpingectomy for uterine fibroids 6 years ago. Ultrasonography and the abdominal and pelvic computed tomography scan detected some solid polycystic masses in the pelvic and abdominal cavities. Diagnoses: The histopathology of the specimen confirmed the diagnosis of LESS in the absence of florid endometriosis. The patient was diagnosed with primary extrauterine endometrial stromal sarcoma at FIGO stage III. Interventions: Surgery and histopathology were performed. Outcome: After surgery, the patient was maintained on leuprorelin acetate microspheres with sustained release for injection at 3.75 mg once every 4 weeks while refusing further radiotherapy. Lessons: The diagnosis of primary LGEESS is challenging mainly because of their unforeseen location and nongynecologic signs and symptoms. Total hysterectomy and bilateral salpingo-oophorectomy are recommended to LGESS, while additional resection for extrauterine disease depends on disease extent and resectability.
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