Molecular subtypes play a pivotal role in guiding preclinical and clinical risk assessment and treatment strategies in cancer. In this study, we extracted whole-tissue transcriptomic data from 1987 ovarian cancer patients spanning 26 independent Gene Expression Omnibus cohorts. A total of four consensus subtypes (C1-C4) were identified, notably, subtype C1 samples exhibited a poor prognosis and higher M2 macrophages infiltration, whereas subtype C2 samples demonstrated the best prognosis and higher CD4 resting T cells infiltration. Additionally, we characterized cancer- and stromal-specific gene expression profiles, and conducted an analysis of ligand-receptor interactions within these compartments. Based on cancer compartment, subtype-specific interactions as well as gene signatures for each molecular subtype were identified. Leveraging single-cell transcriptomic data, we delineated malignant epithelial cells with four molecular subtypes and observed an increase in C1 cell proportions from primary to relapse to metastasis stages, with a corresponding decrease in C2 cell proportions. Furthermore, we investigated subtype-specific interaction with T cells through integrated analysis of bulk and single-cell datasets. Finally, we developed a robust ten-gene risk model based on subtype gene signatures for prognostic evaluation in ovarian cancer, demonstrating its efficacy across independent datasets. In summary, this study systematically explored ovarian cancer molecular subtypes and provided a framework for other cancer types.

Ovarian cancer is one of the most lethal malignant tumors, characterized by high incidence and poor prognosis. Patients relapse occurred in 65–80

AbstractBackgroundUterine corpus endometrial carcinoma (UCEC) ranks sixth among malignant tumors in women and the mortality is still rising. FAT2 gene has been considered to be related to the survival and prognosis of some certain diseases in previous studies, but the FAT2 mutation status in UCEC and its prognostic value has been rarely studied. Hence, the purpose of our study was to explore the role of FAT2 mutations for predicting prognosis and responsiveness to immunotherapy in patients with UCEC.MethodsUCEC samples from the Cancer Genome Atlas database were analyzed. We evaluated the impact of FAT2 gene mutation status and clinicopathological characteristics on the prognosis of UCEC patients and used univariate and multivariate Cox analysis risk scores to independently predict patient overall survival (OS). Tumor mutation burden (TMB) values of the FAT2 mutant and non‐mutant groups were computed by Wilcoxon rank sum test. The correlation of FAT2 mutation and half maximal inhibitory concentration (IC50) values of various anticancer drugs was analyzed. Gene Ontology data and Gene Set Enrichment Analysis (GSEA) were employed to examine the differential expression of genes between the two groups. Finally, a single‐sample GSEA arithmetic was utilized to measure the abundance of tumor‐infiltrating immune cells in UCEC patients.ResultsFAT2 mutations suggested better OS (p < 0.001) and disease‐free survival (DFS) (p = 0.007) in UCEC. The IC50 values of 18 anticancer drugs were upregulated in FAT2 mutation patients (p < 0.05). The TMB and microsatellite instability values of patients with FAT2 mutations were significantly higher (p < 0.001). Next, the Kyoto Encyclopedia of Genes and Genomes functional analysis and GSEA revealed the potential mechanism of FAT2 mutation on the tumorigenesis and progression of UCEC. In addition, in reference to the UCEC microenvironment, the infiltration levels of activated CD4/CD8 T cells (p < 0.001/p = 0.001) and plasmacytoid dendritic cells (p = 0.006) were upregulated in the non‐FAT2 mutation group, and Type 2 T helper cells (p = 0.001) were downregulated in the FAT2 mutation group.ConclusionsUCEC patients with FAT2 mutations have better prognosis and are more likely to respond to immunotherapy. FAT2 mutation may be a valuable predictor for prognosis and responsiveness to immunotherapy in UCEC patients.

Ovarian cancer is the most frequent cause of death among gynecologic malignancies. A total of 80% of patients who have completed platinum-based chemotherapy suffer from relapse and develop resistance within 2 years. In the present study, we obtained patients' complete platinum (cisplatin and carboplatin) medication information from The Cancer Genome Atlas database and then divided them into two categories: resistance and sensitivity. Difference analysis was performed to screen differentially expressed genes (DEgenes) related to platinum response. Subsequently, we annotated DEgenes into the protein–protein interaction network as seed nodes and analyzed them by random walk. Finally, second-ranking protease serine 1 gene (PRSS1) was selected as a candidate gene for verification analysis. PRSS1's expression pattern was continuously studied in Oncomine and cBio Cancer Genomic Portal databases, revealing the key roles of PRSS1 in ovarian cancer formation. Hereafter, we conducted in-depth explorations on PRSS1's platinum response to ovarian cancer through tissue and cytological experiments. Quantitative real-time polymerase chain reaction and Western blot assay results indicated that PRSS1 expression levels in platinum-resistant samples (tissue/cell) were significantly higher than in samples sensitive to platinum. By cell transfection assay, we observed that knockdown of PRSS1 reduced the resistance of ovarian cancer cells to cisplatin. Meanwhile, overexpression of PRSS1 increased the resistance to cisplatin. In conclusion, we identified a novel risk gene PRSS1 related to ovarian cancer platinum response and confirmed its key roles using multiple levels of low-throughput experiments, revealing a new treatment strategy based on a novel target factor for overcoming cisplatin resistance in ovarian cancer.

Ovarian cancer is the most lethal gynaecological cancer, and resistance of platinum-based chemotherapy is the main reason for treatment failure. The aim of the present study was to identify candidate genes involved in ovarian cancer platinum response by analysing genes from homologous recombination and Fanconi anaemia pathways. Associations between these two functional genes were explored in the study, and we performed a random walk algorithm based on reconstructed gene-gene network, including protein-protein interaction and co-expression relations. Following the random walk, all genes were ranked and GSEA analysis showed that the biological functions focused primarily on autophagy, histone modification and gluconeogenesis. Based on three types of seed nodes, the top two genes were utilized as examples. We selected a total of six candidate genes (FANCA, FANCG, POLD1, KDM1A, BLM and BRCA1) for subsequent verification. The validation results of the six candidate genes have significance in three independent ovarian cancer data sets with platinum-resistant and platinum-sensitive information. To explore the correlation between biomarkers and clinical prognostic factors, we performed differential analysis and multivariate clinical subgroup analysis for six candidate genes at both mRNA and protein levels. And each of the six candidate genes and their neighbouring genes with a mutation rate greater than 10% were also analysed by network construction and functional enrichment analysis. In the meanwhile, the survival analysis for platinum-treated patients was performed in the current study. Finally, the RT-qPCR assay was used to determine the performance of candidate genes in ovarian cancer platinum response. Taken together, this research demonstrated that comprehensive bioinformatics methods could help to understand the molecular mechanism of platinum response and provide new strategies for overcoming platinum resistance in ovarian cancer treatment.

目前,对于放疗敏感且失去手术机会的癌症患者而言,同步放化疗是主要的治疗手段,合理的放疗疗效监测指标,可以在很大程度上为癌症患者预后的评估提供参考价值.血小板与淋巴细胞比值(Platelet to lymphocyte ratio,PLR)是评价机体炎症反应的指标之一,与单独评价淋巴细胞和血小板计数相比,可以更准确和敏感地反映患者的炎症状态.已有文献报导PLR与恶性肿瘤放化疗的相关性,且在预后评估方面受到了越来越多的关注.本文将对PLR在恶性肿瘤放化疗预后的研究进展进行阐述.

Long noncoding RNA (lncRNA) can function as a competing endogenous RNA (ceRNA) involved in tumor initiation and progression. However, the prognostic roles of lncRNAs in the integrated analysis of the ceRNA network in ovarian cancer (OVC) are still lacking. This study aimed to identify lncRNAs associated with the prognosis of OVC. Differential expression analysis and WGCNA were used to screen OVC-specific RNAs. A lncRNA-miRNA-mRNA regulatory network consisting of 201 lncRNAs, 85 miRNA and 146 mRNAs was constructed, and functional enrichment and protein-protein network analyses were performed. Then, the OVC-specific RNAs were submitted to Cox regression analysis. Twelve differentially expressed lncRNAs and mRNAs were identified as significantly associated with OS of OVC patients. Meanwhile, 11 lncRNAs (including C4A-AS1, LINC02408, LINC00488) were established as prognostic risk formulas. The low-risk group had better OS and DFS than the high-risk group (P <0.01). Univariate and multivariate Cox regression analyses revealed the 11-lncRNA risk score as an independent prognostic factor. A prognostic nomogram was developed based on independent prognostic factors. Our data provide evidence that the 11-lncRNA signature could serve as an independent prognostic indicator. This study also suggests that these 11 lncRNAs potentially participate in the progression of OVC.

Ovarian cancer (OvCa) causes the highest mortality among all gynaecologic cancers. A large number of mRNA- or miRNA-based signatures were identified for OvCa patient prognosis. However, the comprehensive analysis of function-level prognostic signatures is currently not considered in OvCa. In the present study, we respectively inferred subpathway activities from mRNA and miRNA levels based on high-throughput expression profiles and reconstructed subpathways. Firstly, the activities of two tumour pathways were calculated and the difference between normal and tumour samples were analysed using multiple tumour types. Then, we calculated subpathway activities for OvCa based on the expression profiles from both mRNA and miRNA levels. Furthermore, based on these subpathway activity matrices, we performed bootstrap analysis to obtain sub-training sets and utilized univariate method to identify robust OvCa prognostic subpathways. A comprehensive comparison of subpathway results between these two levels was performed. As a result, we observed subpathway mutual exclusion trend between the levels of mRNA and miRNA, which indicated the necessary of combining mRNA-miRNA levels. Finally, by using ICGC data as testing sets, we utilized two strategies to verify survival predictive power of the mRNA-miRNA combined subpathway signatures and performed comparisons with results from individual levels. It was confirmed that our framework displayed application to identify robust and efficient prognostic signatures for OvCa, and the combined signatures indeed exhibited advantages over individual ones. In the study, we took a step forward in relevant novel integrated functional signatures for OvCa prognosis.

By now,the clinical methods of cancer treatment are mainly surgery,radiotherapy,chemotherapy,and traditional Chinese medicine methods. However,some tumors are concealed due to onset,initial diagnosis and treatment,which have entered the middle and late stage,lost the operation opportunity and impossible to pass accurate surgical staging by assessment of prognosis. Radi-cal concurrent chemoradiotherapy can be used for tumors that are inoperable and sensitive to radiation therapy. Therefore,it has be-come a hot spot to explore accurate and economic indicators to evaluate the prognosis of radiotherapy and chemotherapy. Neutrophil to lymphocyte ratio(NLR)refers to the ratio of neutrophils to lymphocytes in peripheral blood before treatment. As a general indicator of systemic inflammatory response,many studies have confirmed that the relationship between the efficacy of radiotherapy and chemother-apy for tumors provides a new way to evaluate the prognosis of tumors. This article briefly reviews the relationship between NLR and the prognosis of tumor-controlled radiotherapy and chemotherapy.

Although radiotherapy has been widely applied to treating cervical cancer in the clinic, its therapeutic efficacy is often restricted to the radioresistance of cancer cells. Retinoblastoma protein-interacting zinc finger gene 1 (RIZ1) has been suggested as a tumour suppressor gene, whereas its role in cervical cancer with or without radiotherapy has been unclear. In this study, two cervical cancer cell lines, HeLa and SiHa cells, stably transfected with RIZ1 overexpression plasmid were subjected to ionizing radiation, and their survival fractions were calculated by assessing their clonogenic abilities. Our results showed that the forced overexpression of RIZ1 significantly reduced the clonogenic survival rates of both HeLa and SiHa cells exposed to ionizing radiation. By analysing the cell apoptotic status, we found that the RIZ1-overexpressed cervical cancer cells under ionizing radiation were more vulnerable to damage, and more γ-H2AX foci were found in these cells. Furthermore, the volumes of tumour xenografts formed by the RIZ1-overexpressed cells in nude mice under ionizing radiation were smaller than those generated by the control cells. There were more morphological changes, apoptosis cells and lower expression of PCNA in RIZ1-overexpressed tumour tissues of mice after exposure to ionizing radiation. Taken together, our study demonstrates that the overexpression of RIZ1 combined with radiotherapy facilitates apoptosis and DNA damage of cervical cancer cells.

Objective:we aim to determine the relationship between Cell sarcoma (c-Src) expression in patients with EOC and the disease phenotype.Methods:c-Src expression was evaluated using Western blotting analysis in 21 ovarian carcinomas and 4 normal ovarian tissues.Immunohistochemistry was used to evaluate c-Src expression in 134 ovarian carcinomas and 26 normal ovarian tissues.The association between c-Src expression and clinically pathologic characteristics were also assessed in these patients.Results:Our results indicated elevated c-Src protein in EOCs compared with that in normal tissues.The overexpression of c-Src was significantly associated with aggressive features,such as advanced disease stage,poor histological grade,lymph node metastasis,and tumor recurrence (P＜0.05).In addition,the overexpression ofc-Src is significantly associated with EOCs' prognosis.Conclusion:c-Src overexpression was significantly associated with the malignant biological behavior of tumor,suggesting c-Src as a potential preventive target in these patients.