Oxidative stress contributes significantly to cancer development. Recent studies have demonstrated that oxidative stress could alter the epigenome and, in particular, DNA methylation. This study aimed to explore the potential link between oxidative stress and uterine corpus endometrial carcinoma (UCEC). An analysis of RNA-seq data and relevant clinical information was conducted with data from The Cancer Genome Atlas (TCGA), and oxidative stress genes were obtained from Gene Set Enrichment Analysis (GSEA). Differentially expressed genes (DEGs) in normal and tumor groups of UCEC were analyzed using GO and KEGG enrichment analysis. As a result of survival analysis, Lasso regression analysis of DEGs, a risk score model of oxidative stress-related genes (OSRGs) was constructed. Moreover, this study demonstrated that OSRGs are associated with immune cell infiltration in UCEC, suggesting oxidative stress may play a role in UCEC development by activating immune cells. We discovered 136 oxidative stress-related DEGs in UCEC, from which we screened 25 prognostic genes significantly related to the overall survival of UCEC patients. BCL2A1, CASP6, GPX2, HIC1, IL19, MSX1, RNF183, SFN, TRPM2 and HIST1H3C are associated with a good prognosis while CDKN2A, CHAC1, E2F1, GSDME, HMGA1, ITGA7, MCM4, MYBL2, PPIF, S100A1, S100A9, STK26 and TRIB3 are involved in a poor prognosis in UCEC. A 7-OSRGs-based risk score (H3C1, CDKN2A, STK26, TRPM2, E2F1, CHAC1, MSX1) was generated by Lasso regression. Further, an association was found between H3C1, CDKN2A, STK26, TRPM2, E2F1, CHAC1 and MSX1 expression levels and the immune infiltrating cells, including CD8 T cells, NK cells, and mast cells in UCEC. NFYA and RFX5 were speculated as common transcription factors of CDKN2A, TRPM2, E2F1, CHAC1, and MSX1 in UCEC.

Objective: To investigate the prognostic value of immune cells within omental metastases originating from advanced epithelial ovarian cancer (EOC). Methods: We performed immunohistochemical analysis to determine the levels of CD4+/CD8+ tumor-infiltrating lymphocytes (TILs) and CD68+ tumor-associated microphages (TAMs) in omental specimens from 100 patients with advanced EOC. Significant prognostic factors, including immune cells and clinical parameters, were assessed by Kaplan–Meier survival analysis and Cox models. Results: Cox regression analysis showed that elevated levels of CD68+ TAMs and intra-islet CD4+ TILs in omental metastases were the main risk factors associated with worse survival outcomes for advanced EOC. Moreover, the survival analysis of relationships between omental immune cells and favorable clinical predictors revealed additional prognostic stratification information. Conclusion: Omental immune cells (TAMs and TILs) provide alternative prognostic factors in advanced EOC. In contrast to markers of the EOC tumor microenvironment at the primary site, elevated CD68+ TAMs and intra-islet CD4+ TILs in omental metastases serve as negative prognostic markers in advanced EOC and imply an unfavorable outcome.

Background: Primary ovarian mucinous tumors with mural nodules are very rare. The histogenesis of the mural nodules remains unclear. Methods: We investigated the clincopathological and molecular features in 3 cases with mural nodules. Results: Patient 1 was diagnosed as mucinous carcinoma with mural nodules of anaplastic carcinoma that was composed of CK+ and CK7+ spindled cells and polygonal cells with marked pleomorphism. Aberrant p53 staining was found in the mural nodules rather than in the mucinous components. A concordant KRAS mutation (c.35G > A p.G12A) was identified in both mucinous tumors and mural nodules. She died of disease at 44 months. The mural nodule in patient 2 was interpreted as a sarcoma, no other specified. The uniform short spindle cells were separated by abundant myxoid matrix. They were CD10 + , CCND1-, SMA-, and negative for break-apart BCOR, PHF1, and JAZF1 FISH assay. The adenocarcinomatous component harbored LOH at D18S51 and FGA loci while the sarcomatous component had LOH at D19S433. She had lung metastasis at 18 months and was alive without evidence of disease for 40 months. Patient 3 harbored multiple mural nodules that were composed of vimentin+, focal CK+, atypical spindle cells. A diagnosis of sarcoma-like mural nodules was rendered. She was alive with no evidence of disease for 13 months. No hotspot mutant AKT1, KRAS, HRAS, and PI3KCA alleles were found in patients 2 and 3. Conclusions: Mural nodules with anaplastic carcinoma or with true sarcomas may represent the dedifferentiation form of mucinous tumors or collision tumors, respectively. The worrisome histology in sarcoma-like mural nodules necessitates meticulous treatment for these patients.

Tumor progression includes the obtainment of progenitor and stem cell-like features and the gradual loss of a differentiated phenotype. Stemness was defined as the potential for differentiation and self-renewal from the cell of origin. Previous studies have confirmed the effective application of stemness in a number of malignancies. However, the mechanisms underlying the growth and maintenance of multiple myeloma (MM) stem cells remain unclear. We calculated the stemness index for samples of MM by utilizing a novel one-class logistic regression (OCLR) machine learning algorithm and found that mRNA expression-based stemness index (mRNAsi) was an independent prognostic factor of MM. Based on the same cutoff value, mRNAsi could stratify MM patients into low and high groups with different outcomes. We identified 127 stemness-related signatures using weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Functional annotation and pathway enrichment analysis indicated that these genes were mainly involved in the cell cycle, cell differentiation, and DNA replication and repair. Using the molecular complex detection (MCODE) algorithm, we identified 34 pivotal signatures. Meanwhile, we conducted unsupervised clustering and classified the MM cohorts into three MM stemness (MMS) clusters with distinct prognoses. Samples in MMS-cluster3 possessed the highest stemness fractions and the worst prognosis. Additionally, we applied the ESTIMATE algorithm to infer differential immune infiltration among the three MMS clusters. The immune core and stromal score were significantly lower in MMS-cluster3 than in the other clusters, supporting the negative relation between stemness and anticancer immunity. Finally, we proposed a prognostic nomogram that allows for individualized assessment of the 3- and 5-year overall survival (OS) probabilities among patients with MM. Our study comprehensively assessed the MM stemness index based on large cohorts and built a 34-gene based classifier for predicting prognosis and potential strategies for stemness treatment.

Background: Cancer-derived exosomes contribute significantly in intracellular communication, particularly during tumorigenesis. Here, we aimed to identify two immune-related ovarian cancer-derived exosomes (IOCEs) subgroups in ovarian cancer (OC) and establish a prognostic model for OC patients based on immune-related IOCEs. Methods: The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq data, as well as clinical and prognostic information. Consensus clustering analysis was performed to identify two IOCEs-associated subgroups. Kaplan-Meier analysis was used to compare the overall survival (OS) between IOCEs-high and IOCEs-low subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the mechanisms and biological effects of differentially expressed genes (DEGs) between the two subtypes. Besides, an IOCE-related prognostic model of OC was constructed by Lasso regression analysis, and the signature was validated using GSE140082 as the validation set. Results: In total, we obtained 21 differentially expressed IOCEs in OC, and identified two IOCE-associated subgroups by consensus clustering. IOCE-low subgroup showed a favorable prognosis while IOCE-high subgroup had a higher level of immune cell infiltration and immune response. GSEA showed that pathways in cancer and immune response were mainly enriched in IOCE-high subgroup. Thus, IOCE-high subgroup may benefit more in immunotherapy treatment. In addition, we constructed a risk model based on nine IOCE-associated genes (CLDN4, AKT2, CSPG5, ALDOC, LTA4H, PSMA2, PSMA5, TCIRG1, ANO6). Conclusion: We developed a novel stratification system for OV based on IOCE signature, which could be used to estimate the prognosis as well as immunotherapy for OC patient.