Influence of single-cell RNA sequencing data integration on the performance of differential gene expression analysis.

Large-scale comprehensive single-cell experiments are often resource-intensive and require the involvement of many laboratories and/or taking measurements at various times. This inevitably leads to batch effects, and systematic variations in the data that might occur due to different technology platforms, reagent lots, or handling personnel. Such technical differences confound biological variations of interest and need to be corrected during the data integration process. Data integration is a challenging task due to the overlapping of biological and technical factors, which makes it difficult to distinguish their individual contribution to the overall observed effect. Moreover, the choice of integration method may impact the downstream analyses, including searching for differentially expressed genes. From the existing data integration methods, we selected only those that return the full expression matrix. We evaluated six methods in terms of their influence on the performance of differential gene expression analysis in two single-cell datasets with the same biological study design that differ only in the way the measurement was done: one dataset manifests strong batch effects due to the measurements of each sample at a different time. Integrated data were visualized using the UMAP method. The evaluation was done both on individual gene level using parametric and non-parametric approaches for finding differentially expressed genes and on gene set level using gene set enrichment analysis. As an evaluation metric, we used two correlation coefficients, Pearson and Spearman, of the obtained test statistics between reference, test, and corrected studies. Visual comparison of UMAP plots highlighted ComBat-seq, limma, and MNN, which reduced batch effects and preserved differences between biological conditions. Most of the tested methods changed the data distribution after integration, which negatively impacts the use of parametric methods for the analysis. Two algorithms, MNN and Scanorama, gave very poor results in terms of differential analysis on gene and gene set levels. Finally, we highlight ComBat-seq as it led to the highest correlation of test statistics between reference and corrected dataset among others. Moreover, it does not distort the original distribution of gene expression data, so it can be used in all types of downstream analyses.

Fibronectin and Periostin as Prognostic Markers in Ovarian Cancer.

Previously, based on a DNA microarray experiment, we identified a 96-gene prognostic signature associated with the shorter survival of ovarian cancer patients. We hypothesized that some differentially expressed protein-coding genes from this signature could potentially serve as prognostic markers. The present study was aimed to validate two proteins, namely fibronectin (FN1) and periostin (POSTN), in the independent set of ovarian cancer samples. Both proteins are mainly known as extracellular matrix proteins with many important functions in physiology. However, there are also indications that they are implicated in cancer, including ovarian cancer. The expression of these proteins was immunohistochemically analyzed in 108 surgical samples of advanced ovarian cancer (majority: high-grade serous) and additionally on tissue arrays representing different stages of the progression of ovarian and fallopian tube epithelial tumors, from normal epithelia, through benign tumors, to adenocarcinomas of different stages. The correlation with clinical, pathological, and molecular features was evaluated. Kaplan-Meier survival analysis and Cox-proportional hazards models were used to estimate the correlation of the expression levels these proteins with survival. We observed that the higher expression of fibronectin in the tumor stroma was highly associated with shorter overall survival (OS) (Kaplan-Meier analysis, log-rank test p = 0.003). Periostin was also associated with shorter OS (p = 0.04). When we analyzed the combined score, calculated by adding together individual scores for stromal fibronectin and periostin expression, Cox regression demonstrated that this joint FN1&POSTN score was an independent prognostic factor for OS (HR = 2.16; 95% CI: 1.02-4.60; p = 0.044). The expression of fibronectin and periostin was also associated with the source of ovarian tumor sample: metastases showed higher expression of these proteins than primary tumor samples (χ2 test, p = 0.024 and p = 0.032). Elevated expression of fibronectin and periostin was also more common in fallopian cancers than in ovarian cancers. Our results support some previous observations that fibronectin and periostin have a prognostic significance in ovarian cancer. In addition, we propose the joint FN1&POSTN score as an independent prognostic factor for OS. Based on our results, it may also be speculated that these proteins are related to tumor progression and/or may indicate fallopian-epithelial origin of the tumor.

Understanding frailty: a qualitative study of European healthcare policy-makers' approaches to frailty screening and management.

OBJECTIVE: To elicit European healthcare policy-makers' views, understanding and attitudes about the implementation of frailty screening and management strategies and responses to stakeholders' views. DESIGN: Thematic analysis of semistructured qualitative interviews. SETTING: European healthcare policy departments. PARTICIPANTS: Seven European healthcare policy-makers representing the European Union (n=2), UK (n=2), Italy (n=1), Spain (n=1) and Poland (n=1). Participants were sourced through professional networks and the European Commission Authentication Service website and were required to be in an active healthcare policy or decision-making role. RESULTS: Seven themes were identified. Our findings reveal a 'knowledge gap', around frailty and awareness of the malleability of frailty, which has resulted in restricted ownership of frailty by specialists. Policy-makers emphasised the need to recognise frailty as a clinical syndrome but stressed that it should be managed via an integrated and interdisciplinary response to chronicity and ageing. That is, through social co-production. This would require a culture shift in care with redeployment of existing resources to deliver frailty management and intervention services. Policy-makers proposed barriers to a culture shift, indicating a need to be innovative with solutions to empower older adults to optimise their health and well-being, while still fully engaging in the social environment. The cultural acceptance of an integrated care system theme described the complexities of institutional change management, as well as cultural issues relating to working democratically, while in signposting adult care, the need for a personal navigator to help older adults to access appropriate services was proposed. Policy-makers also believed that screening for frailty could be an effective tool for frailty management. CONCLUSIONS: There is potential for frailty to be managed in a more integrated and person-centred manner, overcoming the challenges associated with niche ownership within the healthcare system. There is also a need to raise its profile and develop a common understanding of its malleability among stakeholders, as well as consistency in how and when it is measured.