Comprehensive analysis of consensus molecular subtypes for ovarian cancer from bulk to single-cell perspectives.

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.

The biological roles of CD47 in ovarian cancer progression.

Ovarian cancer is one of the most lethal malignant tumors, characterized by high incidence and poor prognosis. Patients relapse occurred in 65-80% after initial treatment. To date, no effective treatment has been established for these patients. Recently, CD47 has been considered as a promising immunotherapy target. In this paper, we reviewed the biological roles of CD47 in ovarian cancer and summarized the related mechanisms. For most types of cancers, the CD47/Sirpα immune checkpoint has attracted the most attention in immunotherapy. Notably, CD47 monoclonal antibodies and related molecules are promising in the immunotherapy of ovarian cancer, and further research is needed. In the future, new immunotherapy regimens targeting CD47 can be applied to the clinical treatment of ovarian cancer patients.

Identification of WRKY gene family in Dioscorea opposita Thunb. reveals that DoWRKY71 enhanced the tolerance to cold and ABA stress.

WRKY transcription factors constitute one of the largest plant-specific gene families, regulating various aspects of plant growth, development, physiological processes, and responses to abiotic stresses. This study aimed to comprehensively analyze the WRKY gene family of yam (Dioscorea opposita Thunb.), to understand their expression patterns during the growth and development process and their response to different treatments of yam and analyze the function of DoWRKY71 in detail. A total of 25 DoWRKY genes were identified from the transcriptome of yam, which were divided into six clades (I, IIa, IIc, IId, IIe, III) based on phylogenetic analysis. The analysis of conserved motifs revealed 10 motifs, varying in length from 16 to 50 amino acids. Based on real-time quantitative PCR (qRT-PCR) analysis, DoWRKY genes were expressed at different stages of growth and development and responded differentially to various abiotic stresses. The expression level of DoWRKY71 genes was up-regulated in the early stage and then down-regulated in tuber enlargement. This gene showed responsiveness to cold and abiotic stresses, such as abscisic acid (ABA) and methyl jasmonate (MeJA). Therefore, further study was conducted on this gene. Subcellular localization analysis revealed that the DoWRKY71 protein was localized in the nucleus. Moreover, the overexpression of DoWRKY71 enhanced the cold tolerance of transgenic tobacco and promoted ABA mediated stomatal closure. This study presents the first systematic analysis of the WRKY gene family in yam, offering new insights for studying WRKY transcription factors in yam. The functional study of DoWRKY71 lays theoretical foundation for further exploring the regulatory function of the DoWRKY71 gene in the growth and development related signaling pathway of yam.

FAT2 mutation is associated with better prognosis and responsiveness to immunotherapy in uterine corpus endometrial carcinoma.

BACKGROUND: Uterine 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. METHODS: UCEC 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. RESULTS: FAT2 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. CONCLUSIONS: UCEC 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.

Overexpression of DoBAM1 from Yam (Dioscorea opposita Thunb.) Enhances Cold Tolerance in Transgenic Tobacco.

ß-amylase (BAM) plays an important role in plant development and response to abiotic stresses. In this study, 5 DoBAM members were identified in yam (Dioscorea opposita Thunb.). A novel ß-amylase gene BAM1, (named DoBAM1), was isolated from yam varieties Bikeqi and Dahechangyu. The open reading frame (ORF) of DoBAM1 is 2806 bp and encodes 543 amino acids. Subcellular localization analysis indicates that DoBAM1 localizes to the cell membrane and cytoplasm. In the yam variety Dahechangyu, the starch content, ß-amylase activity, and expression of DoBAM1 were characterized and found to all be higher than in Bikeqi. DoBAM1 overexpression in tobacco is shown to promote the accumulation of soluble sugar and chlorophyll content and to increase the activities of peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), and ß-amylase. Under cold treatment, we observed the induced upregulation of DoBAM1 and lower starch content and malondialdehyde (MDA) accumulation than in WT plants. In conclusion, these results demonstrate that DoBAM1 overexpression plays an advanced role in cold tolerance, at least in part by raising the levels of soluble sugars that are capable of acting as osmolytes or antioxidants.

Integrated analysis of a competing endogenous RNA network reveals an 11-lncRNA prognostic signature in ovarian cancer.

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.

The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis.

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.

Comprehensive analysis of mRNA-level and miRNA-level subpathway activities for identifying robust ovarian cancer prognostic signatures.

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.

PRSS1 Upregulation Predicts Platinum Resistance in Ovarian Cancer 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.

Combination of RIZ1 Overexpression and Radiotherapy Contributes to Apoptosis and DNA Damage of HeLa and SiHa Cervical Cancer Cells.

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.

Microbial community structures in an integrated two-phase anaerobic bioreactor fed by fruit vegetable wastes and wheat straw.

The microbial community structures in an integrated two-phase anaerobic reactor (ITPAR) were investigated by 16S rDNA clone library technology. The 75L reactor was designed with a 25L rotating acidogenic unit at the top and a 50L conventional upflow methanogenic unit at the bottom, with a recirculation connected to the two units. The reactor had been operated for 21 stages to co-digest fruit/vegetable wastes and wheat straw, which showed a very good biogas production and decomposition of cellulosic materials. The results showed that many kinds of cellulose and glycan decomposition bacteria related with Bacteroidales, Clostridiales and Syntrophobacterales were dominated in the reactor, with more bacteria community diversities in the acidogenic unit. The methanogens were mostly related with Methanosaeta, Methanosarcina, Methanoculleus, Methanospirillum and Methanobacterium; the predominating genus Methanosaeta, accounting for 40.5%, 54.2%, 73.6% and 78.7% in four samples from top to bottom, indicated a major methanogenesis pathway by acetoclastic methanogenesis in the methanogenic unit. The beta diversity indexes illustrated a more similar distribution of bacterial communities than that of methanogens between acidogenic unit and methanogenic unit. The differentiation of methanogenic community composition in two phases, as well as pH values and volatile fatty acid (VFA) concentrations confirmed the phase separation of the ITPAR. Overall, the results of this study demonstrated that the special designing of ITPAR maintained a sufficient number of methanogens, more diverse communities and stronger syntrophic associations among microorganisms, which made two phase anaerobic digestion of cellulosic materials more efficient.

Using reverse phase high performance liquid chromatography as an alternative to resin fractionation to assess the hydrophobicity of natural organic matter.

Resin fractionation is the most widely used technique to isolate and characterize natural organic matter (NOM) based on its hydrophobicity and hydrophilicity, however, it is also recognized as a time consuming technique. This paper describes the use of reverse phase high performance liquid chromatography (RPHPLC) as a rapid assessment technique to determine the hydrophobicity/hydrophilicity of NOM. The optimum column separation condition was achieved and without the need for concentrating the sample prior to analysis and with good reproducibility of the peak retention time and the peak area. The characterization results were further compared with the traditional resin fractionation technique using DAX-8 and XAD-4 resins. The results demonstrated that the polarities defined by the two methods were different but consistent and also that the fractions absorbed onto XAD-4 were less hydrophobic than those absorbed onto DAX-8. The difference in definition between resin fractionation and RPHPLC were further investigated.

pH modeling for maximum dissolved organic matter removal by enhanced coagulation.

Correlations between raw water characteristics and pH after enhanced coagulation to maximize dissolved organic matter (DOM) removal using four typical coagulants (FeCl3, Al2(SO4)3, polyaluminum chloride (PACl) and high performance polyaluminum chloride (HPAC)) without pH control were investigated. These correlations were analyzed on the basis of the raw water quality and the chemical and physical fractionations of DOM of thirteen Chinese source waters over three seasons. It was found that the final pH after enhanced coagulation for each of the four coagulants was influenced by the content of removable DOM (i.e. hydrophobic and higher apparent molecular weight (AMW) DOM), the alkalinity and the initial pH of raw water. A set of feed-forward semi-empirical models relating the final pH after enhanced coagulation for each of the four coagulants with the raw water characteristics were developed and optimized based on correlation analysis. The established models were preliminarily validated for prediction purposes, and it was found that the deviation between the predicted data and actual data was low. This result demonstrated the potential for the application of these models in practical operation of drinking water treatment plants.

Prediction of DOM removal of low specific UV absorbance surface waters using HPSEC combined with peak fitting.

High performance size exclusion chromatography (HPSEC) is used in water quality research primarily to determine the molecular weight distribution of the dissolved organic matter (DOM), but by applying peak fitting to the chromatogram, this technique can also be used as a tool to model and predict DOM removal. Six low specific UV absorbance (SUVA) source waters were treated using coagulation with alum and both the source and treated water samples were analysed using HPSEC. By comparing the molecular weight profiles of the source and treated waters, it was established that several DOM components were not effectively removed by alum coagulation even after high dosage alum treatment. A peak-fitting technique was applied based on the concept of linking the character (molecular weight profile) of the recalcitrant organics in the treated water with those of the source water. This was then applied to predict DOM treatability by determining the areas of the peaks which were assigned to removable organics from the source water molecular weight profile after peak fitting, and this technique quantified the removable and non-removable organics. The prediction was compared with the actual dissolved organic carbon (DOC) removal determined from jar testing and showed good agreement, with variance between 2% and 10%. This confirmed that this prediction approach, which was originally developed for high SUVA waters, can also be applied successfully to predict DOC removal in low SUVA waters.

Application of advanced characterization techniques to assess DOM treatability of micro-polluted and un-polluted drinking source waters in China.

China has a very complex water supply system which relies on many rivers and lakes. As the population and economic development increases, water quality is greatly impacted by anthropogenic processes. This seriously affects the character of the dissolved organic matter (DOM) and imposes operational challenges to the water treatment facilities in terms of process optimization. The aim of this investigation was to compare selected drinking water sources (raw) with different DOM character, and the respective treated waters after coagulation, using simple organic characterization techniques to obtain a better understanding of the impact of source water quality on water treatment. Results from the analyses of selected water samples showed that the dissolved organic carbon (DOC) of polluted waters is generally higher than that of un-polluted waters, but the specific UV absorbance value has the opposite trend. After resolving the high performance size exclusion chromatography (HPSEC) peak components of source waters using peak fitting, the twelve waters studied can be divided into two main groups (micro-polluted and un-polluted) by using cluster analysis. The DOM removal efficiency (treatability) of these waters has been compared using four coagulants. For water sources allocated to the un-polluted group, traditional coagulants (Al(2)(SO(4))(3) and FeCl(3)) achieved better removal. High performance poly aluminum chloride, a new type of composite coagulant, performed very well and more efficiently for polluted waters. After peak fitting the HPSEC chromatogram of each of the treated waters, average removal efficiency of the profiles can be calculated and these correspond well with DOC and UV removal. This provides a convenient tool to assess coagulation removal and coagulant selection.