IndGOterm: a qualitative method for the identification of individually dysregulated GO terms in cancer.

Individual pathway analysis can dissect heterogeneities among different cancer patients and provide efficient guidelines for individualized therapy. However, the existence of the batch effect brings extensive limitations for the application of many individual methods for pathway analysis. Previously, researchers proposed that methods based on within-sample relative expression ordering (REO) of the genes are notably insensitive to 'batch effects'. In this article, we focus on the Gene Ontology (GO) database and propose an individual qualitative GO term analysis method (IndGOterm) based on the REO of genes. Compared with some current widely used single-sample enrichment analysis methods, such as ssGSEA and GSVA, IndGOterm has a predominance of ignoring the batch effects caused by diverse technologies. Through the survival and drug responses analysis, we found IndGOterm could capture more terms connected to cancer than other single-sample enrichment analysis methods. Furthermore, through the application of IndGOterm, we found some terms that present different dysregulation models that manifest heterogenetic in homologous patients. Collectively, these results attested that IndGOterm could capture useful information from patients and be a useful tool to reveal the intrinsic characteristic of cancer. An open-source R statistical analysis package 'IndGOterm' is available at https://github.com/robert19960424/IndGOterm.

Multilevel prioritization of gene regulators associated with consensus molecular subtypes of colorectal cancer.

Consensus molecular subtypes (CMSs) are emerging as critical factor for prognosis and treatment of colorectal cancer. Gene regulators, including chromatin regulator, RNA-binding protein and transcriptional factor, are critical modulators of cancer hallmark, yet little is known regarding the underlying functional mechanism in CMSs. Herein, we identified a core set of 235 functional gene regulators (FGRs) by integrating genome, epigenome, transcriptome and interactome of CMSs. FGRs exhibited significant multi-omics alterations and impacts on cell lines growth, as well as significantly enriched cancer driver genes and pathways. Moreover, common FGRs played different roles in the context of CMSs. In accordance with the immune characteristics of CMSs, we found that the anti-tumor immune pathways were mainly activated by FGRs (e.g. STAT1 and CREBBP) in CMS1, while inhibited by FGRs in CMS2-4. FGRs mediated aberrant expression of ligands, which bind to receptor on immune cells, and modulated tumor immune microenvironment of subtypes. Intriguingly, systematic exploration of datasets using genomic and transcriptome co-similarity reveals the coordinated manner in FGRs act in CMSs to orchestrate their pathways and patients' prognosis. Expression signatures of the FGRs revealed an optimized CMS classifier, which demonstrated 88% concordance with the gold-standard classifier, but avoiding the influence of sample composition. Overall, our integrative analysis identified FGRs to regulate core tumorigenic processes/pathways across CMSs.

cPLA2α reversibly regulates different subsets of cancer stem cells transformation in cervical cancer.

Cervical cancer stem cells (CCSCs) are considered major causes of chemoresistance/radioresistance and metastasis. Although several cell surface antigens have been identified in CCSCs, these markers vary among tumors because of CSC heterogeneity. However, whether these markers specifically distinguish CCSCs with different functions is unclear. Here, we demonstrated that CCSCs exist in two biologically distinct phenotypes characterized by different levels of cytosolic phospholipase A2α (cPLA2α) expression. Overexpression of cPLA2α results in a CD44+ CD24- phenotype associated with mesenchymal traits, including increased invasive and migration abilities, whereas CCSCs with cPLA2α downregulation express CD133 and show quiescent epithelial characteristics. In addition, cPLA2α regulates the reversible transition between mesenchymal and epithelial CCSC states through PKCζ, an atypical protein kinase C, which governs cancer cell state changes and the maintenance of various embryonic stem cell characteristics, further inhibiting ß-catenin-E-cadherin interaction in membrane and promoting ß-catenin translocation into the nucleus to affect the transcriptional regulation of stemness signals. We propose that reversible transitions between mesenchymal and epithelial CCSC states regulated by cPLA2α are necessary for cervical cancer metastasis and recurrence. Thus, cPLA2α might be an attractive therapeutic target for eradicating different states of CCSCs to eliminate tumors more effectively.

Identification of EMT-related high-risk stage II colorectal cancer and characterisation of metastasis-related genes.

BACKGROUND: Our laboratory previously reported an individual-level prognostic signature for patients with stage II colorectal cancer (CRC). However, this signature was not applicable for RNA-sequencing datasets. In this study, we constructed a robust epithelial-to-mesenchymal transition (EMT)- related gene pair prognostic signature. METHODS: Based on EMT-related genes, metastasis-associated gene pairs were identified between metastatic and non-metastatic samples. Then, we selected prognosis-associated gene pairs, which were significantly correlated with disease-free survival of stage II CRC using multivariate Cox regression model, as the EMT-related prognosis signature. RESULTS: An EMT-related signature composed of fifty-one gene pairs (51-GPS) for prediction-relapse risk of patients with stage II CRC was developed, whose prognostic efficiency was validated in independent datasets. Moreover, 51-GPS achieved better predictive performance than other reported signatures, including a commercial signature Oncotype Dx colon cancer and an immune-related gene pair signature. Besides, EMT-related functional gene sets achieved high enrichment scores in high-risk samples. Especially, loss-of-function antisense approach showed that DEGs between the predicted two clusters were metastasis-related. CONCLUSIONS: The EMT-related gene pair signature can identify the high relapse-risk patients with stage II CRC, which can facilitate individualised management of patients.

Ovarian Sertoli-Leydig cell tumor: a report of seven cases and a review of the literature.

The aim of this study was to investigate the clinicopathologic features, treatment and outcome of seven patients with an ovarian Sertoli-Leydig cell tumor (SLCT). Five patients presented with feminization, two with accompanying virilization. One presented with amenorrhea alone. Three of the five patients showing feminization symptoms had endocrine-related diseases. Histologically, five tumors were well differentiated, the other two were poorly differentiated. The latter two patients were misdiagnosed as having an ovarian epithelial carcinoma or granulosa cell tumor from frozen sections. Immunohistochemistry showed that the tumors were calretinin-positive in two patients and one was inhibin-positive. Four patients underwent total abdominal hysterectomy and bilateral salpingo-oophorectomy(TAH/BSO) and two were treated by unilateral salpingo-oophorectomy. Among them, two patients received adjuvant chemotherapy. Six patients were free of disease in a follow-up of 2-34 years and one achieved a pregnancy. The remaining patient recurred 4 years later. Feminization as well as virilization might provide important clues for a preoperative diagnosis. Histological misdiagnosis is probable in poorly differentiated tumors. Conservative surgery including retention of fertility can be considered. However, the tendency for recurrence in poorly differentiated tumors should be considered.

A case series on the efficacy and safety of a PD-1 inhibitor combined with antiangiogenic agents in the treatment of recurrent MSI-H endometrial cancer.

Background: Endometrial cancer (EC) is one of the most common gynecological malignancies in developed countries worldwide. The treatment of recurrent endometrial cancer is a very difficult problem in clinical work. Studies on patients with recurrent EC microsatellite instability-high (MSI-H) are very rare. The objective of this study is to initially evaluate the therapeutic effect of a PD-1 inhibitor combined with antiangiogenic agents in the treatment of recurrent MSI-H endometrial cancer. Methods: Eight patients with recurrent MSI-H endometrial cancer were recruited from Tianjin Medical University Cancer Institute and Hospital from July 2019 to July 2021, and their median age was 55.3 (range, 46-62) years. All patients experienced recurrence after surgical treatment, and the median recurrence and metastasis time was 6.6 (range, 4-10) months. The pathological types were all endometrioid carcinomas. PD-1 inhibitors were selected from camrelizumab or pembrolizumab, and antiangiogenic targeted agents were selected from apatinib or anlotinib. Results: The median follow-up time was 11.0 (range, 5-19) months. In the case series, all 8 cases could be evaluated for curative effect with complete response in 4 cases and partial response in 4 cases. The overall objective response rate was 100%. Conclusions: PD-1 inhibitors combined with antiangiogenic agents may have good therapeutic effects on patients with recurrent MSI-H endometrial cancer and may become an important method for the treatment of recurrent endometrial cancer in the future.

Epigenetic-related gene mutations serve as potential biomarkers for immune checkpoint inhibitors in microsatellite-stable colorectal cancer.

Background: Combination therapy with immune checkpoint inhibitors (ICIs) may benefit approximately 10-20% of microsatellite-stable colorectal cancer (MSS-CRC) patients. However, there is a lack of optimal biomarkers. This study aims to understand the predictive value of epigenetic-related gene mutations in ICIs therapy in MSS-CRC patients. Methods: We analyzed DNA sequences and gene expression profiles from The Cancer Genome Atlas (TCGA) to examine their immunological features. The Harbin Medical University Cancer Hospital (HMUCH) clinical cohort of MSS-CRC patients was used to validate the efficacy of ICIs in patients with epigenetic-related gene mutations (Epigenetic_Mut). Results: In TCGA, 18.35% of MSS-CRC patients (78/425) had epigenetic-related gene mutations. The Epigenetic_Mut group had a higher tumor mutation burden (TMB) and frameshift mutation (FS_mut) rates. In all MSS-CRC samples, Epigenetic_Mut was elevated in the immune subtype (CMS1) and had a strong correlation with immunological features. Epigenetic_Mut was also associated with favorable clinical outcomes in MSS-CRC patients receiving anti-PD-1-based therapy from the HMUCH cohort. Using immunohistochemistry and flow cytometry, we demonstrated that Epigenetic_Mut samples were associated with increased anti-tumor immune cells both in tumor tissues and peripheral blood. Conclusion: MSS-CRC patients with epigenetic regulation impairment exhibit an immunologically active environment and may be more susceptible to treatment strategies based on ICIs.

Integrated multi-omics analysis reveals miR-20a as a regulator for metabolic colorectal cancer.

Single-driver molecular events specific to the metabolic colorectal cancer (CRC) have not been clearly elucidated. Herein, we identified 12 functional miRNAs linked to activated metabolism by integrating multi-omics features in metabolic CRC. These miRNAs exhibited significantly enriched CRC driver miRNAs, significant impacts on CRC cell growth and significantly correlated metabolites. Importantly, miR-20a is minimally expressed in normal colorectal tissues but highly expressed in metabolic CRC, suggesting the potential therapeutic target. Bioinformatics analyses further revealed miR-20a as the most powerful determinant that regulates a cascade of dysregulated events, including Wnt signaling pathway, core enzymes involved in FA metabolism program and triacylglycerol abundances. In vitro assays demonstrated that elevated miR-20a up-regulated FA synthesis enzymes via Wnt/ß-catenin signaling, and finally promoted proliferative and migration of metabolic CRC cells. Overall, our study revealed that miR-20a promoted progression of metabolic CRC by regulating FA metabolism and served as a potential target for preventing tumor metastasis.

StemSC: a cross-dataset human stemness index for single-cell samples.

BACKGROUND: Stemness is defined as the potential of cells for self-renewal and differentiation. Many transcriptome-based methods for stemness evaluation have been proposed. However, all these methods showed low negative correlations with differentiation time and can't leverage the existing experimentally validated stem cells to recognize the stem-like cells. METHODS: Here, we constructed a stemness index for single-cell samples (StemSC) based on relative expression orderings (REO) of gene pairs. Firstly, we identified the stemness-related genes by selecting the genes significantly related to differentiation time. Then, we used 13 RNA-seq datasets from both the bulk and single-cell embryonic stem cell (ESC) samples to construct the reference REOs. Finally, the StemSC value of a given sample was calculated as the percentage of gene pairs with the same REOs as the ESC samples. RESULTS: We validated the StemSC by its higher negative correlations with differentiation time in eight normal datasets and its higher positive correlations with tumor dedifferentiation in three colorectal cancer datasets and four glioma datasets. Besides, the robust of StemSC to batch effect enabled us to leverage the existing experimentally validated cancer stem cells to recognize the stem-like cells in other independent tumor datasets. And the recognized stem-like tumor cells had fewer interactions with anti-tumor immune cells. Further survival analysis showed the immunotherapy-treated patients with high stemness had worse survival than those with low stemness. CONCLUSIONS: StemSC is a better stemness index to calculate the stemness across datasets, which can help researchers explore the effect of stemness on other biological processes.

Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer.

Endometrial cancer (EC) is the gynecological tumor with the highest incidence. In recent years, it has been proved that necroptosis is a method of cell death related to EC. However, the expression of necroptosis-related miRNA in EC and its correlation with prognosis still ill-defined. Use the Cancer Genome Atlas (TCGA) cohort to obtain prognostic data and related clinical data for ECs and normal endometrium tissues. In this study, we identified three necroptotic regulatory miRNAs that are necroptosis-related and survival-related miRNAs (DENSMs) between normal endometrium tissues and EC from 13 necroptosis-related miRNAs. The three DENSMs signature was built to develop prognostic model and classified all EC patients into a high or low risk group. EC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (p = 0.0242), and the risk score was found to be an independent prognosis factor for predicting the OS of EC patients (p = 0.0254) in multivariate Cox regression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed dephosphorylation, microtubule, protein serine/threonine kinase activity, PI3K-Akt signaling pathway and MAPK signaling pathway are closely related to it. In conclusion, the risk prediction model based on necroptosis-related miRNAs can effectively predict the prognosis of EC patients.

Evaluation of FGFR1 as a diagnostic biomarker for ovarian cancer using TCGA and GEO datasets.

BACKGROUND: Malignant ovarian cancer is associated with the highest mortality of all gynecological tumors. Designing therapeutic targets that are specific to OC tissue is important for optimizing OC therapies. This study aims to identify different expression patterns of genes related to FGFR1 and the usefulness of FGFR1 as diagnostic biomarker for OC. METHODS: We collected data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. In the TCGA cohort we analyzed clinical information according to patient characteristics, including age, stage, grade, longest dimension of the tumor and the presence of a residual tumor. GEO data served as a validation set. We obtained data on differentially expressed genes (DEGs) from the two microarray datasets. We then used gene set enrichment analysis (GSEA) to analyze the DEG data in order to identify enriched pathways related to FGFR1. RESULTS: Differential expression analysis revealed that FGFR1 was significantly downregulated in OC specimens. 303 patients were included in the TCGA cohort. The GEO dataset confirmed these findings using information on 75 Asian patients. The GSE105437 and GSE12470 database highlighted the significant diagnostic value of FGFR1 in identifying OC (AUC = 1, p = 0.0009 and AUC = 0.8256, p = 0.0015 respectively). CONCLUSIONS: Our study examined existing TCGA and GEO datasets for novel factors associated with OC and identified FGFR1 as a potential diagnostic factor. Further investigation is warranted to characterize the role played by FGFR1 in OC.

A Cancer-Specific Qualitative Method for Estimating the Proportion of Tumor-Infiltrating Immune Cells.

Tumor-infiltrating immune cells are important components in the tumor microenvironment (TME) and different types of these cells exert different effects on tumor development and progression; these effects depend upon the type of cancer involved. Several methods have been developed for estimating the proportion of immune cells using bulk transcriptome data. However, there is a distinct lack of methods that are capable of predicting the immune contexture in specific types of cancer. Furthermore, the existing methods are based on absolute gene expression and are susceptible to experimental batch effects, thus resulting in incomparability across different datasets. In this study, we considered two common neoplasms as examples (colorectal cancer [CRC] and melanoma) and introduced the Tumor-infiltrating Immune Cell Proportion Estimator (TICPE), a cancer-specific qualitative method for estimating the proportion of tumor-infiltrating immune cells. The TICPE was based on the relative expression orderings (REOs) of gene pairs within a sample and is notably insensitive to batch effects. Performance evaluation using public expression data with mRNA mixtures, single-cell RNA-Seq (scRNA-Seq) data, immunohistochemistry data, and simulated bulk RNA-seq samples, indicated that the TICPE can estimate the proportion of immune cells with levels of accuracy that are clearly superior to other methods. Furthermore, we showed that the TICPE could effectively detect prognostic signals in patients with tumors and changes in the fractions of immune cells during immunotherapy in melanoma. In conclusion, our work presented a unique novel method, TICPE, to estimate the proportion of immune cells in specific cancer types and explore the effect of the infiltration of immune cells on the efficacy of immunotherapy and the prognosis of cancer. The source code for TICPE is available at https://github.com/huitingxiao/TICPE.

Chinese Nurses' Preferences for and Attitudes About e-Learning in Continuing Education: A Correlational Study.

BACKGROUND: This study aimed to examine nurses' preferences for and attitudes toward e-learning, identify factors that motivated or discouraged their e-learning participation, and also find the relationship between the nurse's attitude and their characteristics. METHOD: A total of 534 RNs from eight hospitals in Shanghai were recruited. Data were collected using a questionnaire that consisted of e-learning experiences, barriers, motivating factors, learning preferences, and attitudes toward e-learning. RESULTS: Flexibility was the most important motivating factor and lack of time was the most common barrier to their participating in e-learning. Participants who had no e-learning experiences reported more barriers about lack of familiarity with e-learning and e-learning platforms. Nearly half of the participants exhibited positive attitudes toward e-learning. Regression analysis identified that nurses who were married, used computers frequently, and worked in rural hospitals were associated with more positive attitudes toward e-learning. CONCLUSION: Nurse educators and managers could provide more opportunities for nurses to increase their familiarity with online education technology and develop more high-quality online courses to meet nurses' learning needs. [J Contin Educ Nurs. 2020;51(2):87-96.].

Nurses' Attitudes toward, and Needs for Online Learning: Differences between Rural and Urban Hospitals in Shanghai, East China.

Health professionals need continuing education to maintain their qualifications and competency. Online learning increases the accessibility and flexibility of continuing education. Assessment of nurses' attitudes toward, and needs for, online learning can provide suggestions regarding learning program design and delivery. This study aimed to evaluate Chinese nurses' attitudes toward, and needs for, online learning, and to explore the differences in attitudes and needs between nurses working in rural and urban hospitals. This work is a secondary analysis of a multicenter cross-sectional study conducted in Shanghai in 2015 (n = 550). Multiple regression techniques were used to determine the factors associated with nurses' attitudes toward, and needs for, online learning. Results showed that nurses in rural hospitals had more positive attitudes toward online learning (102.7 ± 14.2) than those in urban hospitals (98.3 ± 12.9) (p < 0.001). For rural hospitals, nurses who could use computers and access the internet in their workplace reported more positive attitudes than those who could not. For urban hospitals, nurse educators showed significantly more positive attitudes than others. Communication skills (86.5%) and patient education (86.3%) were the most commonly-reported learning needs for nurses regardless of their working settings. Chinese nurses were willing to adopt online learning as a continuing education method. Nurses working in rural hospitals displayed more positive attitudes toward, and needs for, online learning than those working in urban hospitals. Nursing educators and managers should develop online learning programs and provide appropriate support to fulfill nurses' learning needs, especially for those working in rural healthcare settings.

Ovarian cancer stem cell-specific gene expression profiling and targeted drug prescreening.

Cancer stem cells, with unlimited self-renewal potential and other stem cell characteristics, occur in several types of cancer, including ovarian cancer (OvC). Although CSCs can cause tumor initiation, malignant proliferation, relapse and multi-drug resistance, ways to eliminate them remain unknown. In the present study, we compared ovarian cancer stem cell (OVCSC) expression profiles in normal ovarian surface epithelium and ovarian cells from patients with advanced disease to identify key pathways and specific molecular signatures involved in OVC progression and to prescreen candidate small-molecule compounds with anti-OVCSC activity. Comparison of genome-wide expression profiles of OvC stemness groups with non-stemness controls revealed 6495, 1347 and 509 differentially expressed genes in SDC, SP1 and SP2 groups, respectively, with a cut-off of fold-change set at >1.5 and P<0.05. NAB1 and NPIPL1 were commonly upregulated whereas PROS1, GREB1, KLF9 and MTUS1 were commonly downregulated in all 3 groups. Most differentially expressed genes consistently clustered with molecular functions such as protein receptor binding, kinase activity and chemo-repellent activity. These genes regulate cellular components such as centrosome, plasma membrane receptors, and basal lamina, and may participate in biological processes such as cell cycle regulation, chemoresistance and stemness induction. Key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways such as ECM receptor, ErbB signaling, endocytosis and adherens junction pathways were enriched. Gene co-expression extrapolation screening by the Connectivity Map revealed several small-molecule compounds (such as SC-560, disulfiram, thapsigargin, esculetin and cinchonine) with potential anti-OVCSC properties targeting OVCSC signature genes. We identified several key CSC features and specific regulation networks in OVCSCs and predicted several small molecules with potential anti-OVCSC pharmacological properties, which may aid the development of OVCSC-specific drugs.