Dimension reduction, cell clustering, and cell-cell communication inference for single-cell transcriptomics with DcjComm.

Advances in single-cell transcriptomics provide an unprecedented opportunity to explore complex biological processes. However, computational methods for analyzing single-cell transcriptomics still have room for improvement especially in dimension reduction, cell clustering, and cell-cell communication inference. Herein, we propose a versatile method, named DcjComm, for comprehensive analysis of single-cell transcriptomics. DcjComm detects functional modules to explore expression patterns and performs dimension reduction and clustering to discover cellular identities by the non-negative matrix factorization-based joint learning model. DcjComm then infers cell-cell communication by integrating ligand-receptor pairs, transcription factors, and target genes. DcjComm demonstrates superior performance compared to state-of-the-art methods.

Deciphering cell-cell communication at single-cell resolution for spatial transcriptomics with subgraph-based graph attention network.

The inference of cell-cell communication (CCC) is crucial for a better understanding of complex cellular dynamics and regulatory mechanisms in biological systems. However, accurately inferring spatial CCCs at single-cell resolution remains a significant challenge. To address this issue, we present a versatile method, called DeepTalk, to infer spatial CCC at single-cell resolution by integrating single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data. DeepTalk utilizes graph attention network (GAT) to integrate scRNA-seq and ST data, which enables accurate cell-type identification for single-cell ST data and deconvolution for spot-based ST data. Then, DeepTalk can capture the connections among cells at multiple levels using subgraph-based GAT, and further achieve spatially resolved CCC inference at single-cell resolution. DeepTalk achieves excellent performance in discovering meaningful spatial CCCs on multiple cross-platform datasets, which demonstrates its superior ability to dissect cellular behavior within intricate biological processes.

Anti-CTLA-4 m2a Antibody Exacerbates Cardiac Injury in Experimental Autoimmune Myocarditis Mice By Promoting Ccl5-Neutrophil Infiltration.

The risk for suffering immune checkpoint inhibitors (ICIs)-associated myocarditis increases in patients with pre-existing conditions and the mechanisms remain to be clarified. Spatial transcriptomics, single-cell RNA sequencing, and flow cytometry are used to decipher how anti-cytotoxic T lymphocyte antigen-4 m2a antibody (anti-CTLA-4 m2a antibody) aggravated cardiac injury in experimental autoimmune myocarditis (EAM) mice. It is found that anti-CTLA-4 m2a antibody increases cardiac fibroblast-derived C-X-C motif chemokine ligand 1 (Cxcl1), which promots neutrophil infiltration to the myocarditic zones (MZs) of EAM mice via enhanced Cxcl1-Cxcr2 chemotaxis. It is identified that the C-C motif chemokine ligand 5 (Ccl5)-neutrophil subpopulation is responsible for high activity of cytokine production, adaptive immune response, NF-κB signaling, and cellular response to interferon-gamma and that the Ccl5-neutrophil subpopulation and its-associated proinflammatory cytokines/chemokines promoted macrophage (Mφ) polarization to M1 Mφ. These altered infiltrating landscape and phenotypic switch of immune cells, and proinflammatory factors synergistically aggravated anti-CTLA-4 m2a antibody-induced cardiac injury in EAM mice. Neutralizing neutrophils, Cxcl1, and applying Cxcr2 antagonist dramatically alleviates anti-CTLA-4 m2a antibody-induced leukocyte infiltration, cardiac fibrosis, and dysfunction. It is suggested that Ccl5-neutrophil subpopulation plays a critical role in aggravating anti-CTLA-4 m2a antibody-induced cardiac injury in EAM mice. This data may provide a strategic rational for preventing/curing ICIs-associated myocarditis.

A comparative analysis of TCR immune repertoire in COVID-19 patients.

The coronavirus disease 2019 (COVID-19) has merged as a global health threat since its outbreak in December 2019. Despite widespread recognition, there has been a paucity of studies focusing on the T cell receptor (TCR) bias in adaptive immunity induced by SARS-CoV-2. This research conducted a comparative analysis of the TCR immune repertoire to identify notable αß TCR bias sequences associated with the SARS-CoV-2 virus antigen. The present study encompassed 73 symptomatic COVID-19 patients, categorized as moderate/mild or severe/critical, along with 9 healthy controls. Our findings revealed specific TCR chains prominently utilized by moderate and severe patients, identified as TRAV30-J34-TRBV3-1-J2-7 and TRAV12-3-J6-TRBV28-J1-1, respectively. Additionally, our research explored critical TCR preferences in the bronchoalveolar lavage fluid (BALF) of COVID-19 patients at various disease stages. Indeed, monitoring the dynamics of immune repertoire changes in COVID-19 patients could serve as a crucial biomarker for predicting disease progression and recovery. Furthermore, the study explored TCR bias in both peripheral blood mononuclear cells (PBMCs) and BALF. The most common αß VJ pair observed in BALF was TRAV12-3-J18-TRBV7-6-J2-7. In addition, a comparative analysis with the VDJdb database indicated that the HLA-A*02:01 allele exhibited the widest distribution and highest frequency in COVID-19 patients across different periods. This comprehensive examination provided a global characterization of the TCR immune repertoire in COVID-19 patients, contributing significantly to our understanding of TCR bias induced by SARS-CoV-2.

A comprehensive review of the botany, phytochemistry, pharmacology, and toxicology of Murrayae Folium et Cacumen.

Ethnopharmacological relevance: Murrayae Folium et Cacumen (MFC) is a plant considered to be a traditional Chinese medicine with culinary value as well. The dry leaves and twigs of Murraya paniculata and M. exotica are used to treat stomach aches, rheumatism, toothaches, swelling, and insect and snake bites. They are also used to prepare spicy chicken dishes. Aim of the review: This review comprehensively summarizes the available information on the botanical characterization, phytochemistry, pharmacological activities, pharmacodynamics, pharmacokinetics, and toxicity of MFC. Methods: Relevant scientific literature up to August 2023 was included in the study. Chinese and English studies on MFC were collected from databases, including PubMed, Elsevier, Web of Science, Springer, Science Direct, Wiley, ACS, and CNKI (Chinese). Doctoral and Master's dissertations were also included. Results: In total, 720 compounds have been identified and reported in the literature, including flavonoids, coumarins, alkaloids, sterols, phenylpropenols, organic acids, spirocyclopentenones, and volatile oils. Flavonoids and coumarins are the two most important bioactive compounds responsible for these pharmacological activities. MFC has anti-inflammatory, anti-bacterial, anti-microbial, anti-diabetic, anti-tumor, anti-oxidant, anti-depressant, potential anti-Alzheimer's disease, chondroprotective, and analgesic properties. The pharmacological effects include interrupting the STAT3/NF-κB/COX-2 and EGFR signaling pathways, downregulating EpCAM expression, inhibiting NF-κB and ERK signals, inhibiting the EP/cAMP/PKA signaling pathway and miR-29a/Wnt/ß-catenin signaling activity, and upregulating Foxo3a expression. Conclusion: This review demonstrates that the chemical constituents, pharmacological activities, pharmacodynamics, pharmacokinetics, and toxicity of MFC support its use in traditional Chinese botanical medicines. MFC contains a wide range of chemical compounds. Flavonoids and coumarins promote strong pharmacological activity and, are low-toxicity natural phytomedicines that are widely used in medicine, food, ornamentation, and cosmetics, making MFC a promising compound for development and use in the treatment of several medical conditions.

The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood.

T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stage. Here, we developed the deep learning framework iCanTCR to identify patients with cancer based on the TCR repertoire. The iCanTCR framework uses TCRß sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2,000 publicly available TCR repertoires from 11 types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish patients with cancer from noncancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an AUC of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for noninvasive cancer diagnosis. SIGNIFICANCE: Development of a deep learning-based method for multicancer detection using the TCR repertoire in the peripheral blood establishes the potential of evaluating circulating immune signals for noninvasive early cancer detection.

Functional requirement of alternative splicing in epithelial-mesenchymal transition of pancreatic circulating tumor.

Circulating tumor cells (CTCs) that undergo epithelial-to-mesenchymal transition (EMT) can provide valuable information regarding metastasis and potential therapies. However, current studies on the EMT overlook alternative splicing. Here, we used single-cell full-length transcriptome data and mRNA sequencing of CTCs to identify stage-specific alternative splicing of partial EMT and mesenchymal states during pancreatic cancer metastasis. We classified definitive tumor and normal epithelial cells via genetic aberrations and demonstrated dynamic changes in the epithelial-mesenchymal continuum in both epithelial cancer cells and CTCs. We provide the landscape of alternative splicing in CTCs at different stages of EMT, uncovering cell-type-specific splicing patterns and splicing events in cell surface proteins suitable for therapies. We show that MBNL1 governs cell fate through alternative splicing independently of changes in gene expression and affects the splicing pattern during EMT. We found a high frequency of events that contained multiple premature termination codons and were enriched with C and G nucleotides in close proximity, which influence the likelihood of stop codon readthrough and expand the range of potential therapeutic targets. Our study provides insights into the EMT transcriptome's dynamic changes and identifies potential diagnostic and therapeutic targets in pancreatic cancer.

Metabonomics and Transcriptomics Analyses Reveal the Development Process of the Auditory System in the Embryonic Development Period of the Small Yellow Croaker under Background Noise.

Underwater noise pollution has become a potential threat to aquatic animals in the natural environment. The main causes of such pollution are frequent human activities creating underwater environmental noise, including commercial shipping, offshore energy platforms, scientific exploration activities, etc. However, in aquaculture environments, underwater noise pollution has also become an unavoidable problem due to background noise created by aquaculture equipment. Some research has shown that certain fish show adaptability to noise over a period of time. This could be due to fish's special auditory organ, i.e., their "inner ear"; meanwhile, otoliths and sensory hair cells are the important components of the inner ear and are also essential for the function of the auditory system. Recently, research in respect of underwater noise pollution has mainly focused on adult fish, and there is a lack of the research on the effects of underwater noise pollution on the development process of the auditory system in the embryonic development period. Thus, in this study, we collected embryo-larval samples of the small yellow croaker (Larimichthys polyactis) in four important stages of otic vesicle development through artificial breeding. Then, we used metabonomics and transcriptomics analyses to reveal the development process of the auditory system in the embryonic development period under background noise (indoor and underwater environment sound). Finally, we identified 4026 differentially expressed genes (DEGs) and 672 differential metabolites (DMs), including 37 DEGs associated with the auditory system, and many differences mainly existed in the neurula stage (20 h of post-fertilization/20 HPF). We also inferred the regulatory mode and process of some important DEGs (Dnmt1, CPS1, and endothelin-1) in the early development of the auditory system. In conclusion, we suggest that the auditory system development of L. polyactis begins at least in the neurula stage or earlier; the other three stages (tail bud stage, caudal fin fold stage, and heart pulsation stage, 28-35 HPF) mark the rapid development period. We speculate that the effect of underwater noise pollution on the embryo-larval stage probably begins even earlier.

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data.

MOTIVATION: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify CCIs from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity. RESULTS: Here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively. Powered by the flexible and easy-to-use software, DeepCCI can provide the one-stop solution to discover meaningful intercellular interactions and build CCI networks from scRNA-seq data. AVAILABILITY AND IMPLEMENTATION: The source code of DeepCCI is available online at https://github.com/JiangBioLab/DeepCCI.

Research progress of plant-derived natural alkaloids in central nervous system diseases.

Central nervous system (CNS) disease is one of the most important causes of human death. Because of their complex pathogenesis, more and more attention has been paid to them. At present, drug treatment of the CNS is the main means; however, most drugs only relieve symptoms, and some have certain toxicity and side effects. Natural compounds derived from plants can provide safer and more effective alternatives. Alkaloids are common nitrogenous basic organic compounds found in nature, which exist widely in many kinds of plants and have unique application value in modern medicine. For example, Galantamine and Huperzine A from medicinal plants are widely used drugs on the market to treat Alzheimer's disease. Therefore, the main purpose of this review is to provide the available information on natural alkaloids with the activity of treating central nervous system diseases in order to explore the trends and perspectives for the further study of central nervous system drugs. In this paper, 120 alkaloids with the potential effect of treating central nervous system diseases are summarized from the aspects of sources, structure types, mechanism of action and structure-activity relationship.

A multifactorial analysis of FAP to regulate gastrointestinal cancers progression.

Background: Fibroblast activation protein (FAP) is a cell-surface serine protease that has both dipeptidyl peptidase as well as endopeptidase activities and could cleave substrates at post-proline bond. Previous findings showed that FAP was hard to be detected in normal tissues but significantly up-regulated in remodeling sites like fibrosis, atherosclerosis, arthritis and embryonic tissues. Though increasing evidence has demonstrated the importance of FAP in cancer progression, no multifactorial analysis has been developed to investigate its function in gastrointestinal cancers until now. Methods: By comprehensive use of datasets from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), scTIME Portal and Human Protein Atlas (HPA), we evaluated the carcinogenesis potential of FAP in gastrointestinal cancers, analyzing the correlation between FAP and poor outcomes, immunology in liver, colon, pancreas as well as stomach cancers. Then liver cancer was selected as example to experimentally validate the pro-tumor and immune regulative role of FAP in gastrointestinal cancers. Results: FAP was abundantly expressed in gastrointestinal cancers, such as LIHC, COAD, PAAD and STAD. Functional analysis indicated that the highly-expressed FAP in these cancers could affect extracellular matrix organization process and interacted with genes like COL1A1, COL1A2, COL3A1 and POSTN. In addition, it was also observed that FAP was positively correlated to M2 macrophages infiltration across these cancers. To verify these findings in vitro, we used LIHC as example and over-expressed FAP in human hepatic stellate LX2 cells, a main cell type that produce FAP in tumor tissues, and then investigate its role on LIHC cells as well as macrophages. Results showed that the medium from FAP-over-expressed LX2 cells could significantly promote the motility of MHCC97H and SK-Hep1 LIHC cells, increase the invasion of THP-1 macrophages and induce them into pro-tumor M2 phenotype. Conclusion: In summary, we employed bioinformatic tools and experiments to perform a comprehensive analysis about FAP. Up-regulation of FAP in gastrointestinal cancers was primarily expressed in fibroblasts and contributes to tumor cells motility, macrophages infiltration and M2 polarization, revealing the multifactorial role of FAP in gastrointestinal cancers progression.

Natural epidithiodiketopiperazine alkaloids as potential anticancer agents: Recent mechanisms of action, structural modification, and synthetic strategies.

Cancer has become a grave health crisis that threatens the lives of millions of people worldwide. Because of the drawbacks of the available anticancer drugs, the development of novel and efficient anticancer agents should be encouraged. Epidithiodiketopiperazine (ETP) alkaloids with a 2,5-diketopiperazine (DKP) ring equipped with transannular disulfide or polysulfide bridges or S-methyl moieties constitute a special subclass of fungal natural products. Owing to their privileged sulfur units and intriguing architectural structures, ETP alkaloids exhibit excellent anticancer activities by regulating multiple cancer proteins/signaling pathways, including HIF-1, NF-κB, NOTCH, Wnt, and PI3K/AKT/mTOR, or by inducing cell-cycle arrest, apoptosis, and autophagy. Furthermore, a series of ETP alkaloid derivatives obtained via structural modification showed more potent anticancer activity than natural ETP alkaloids. To solve supply difficulties from natural resources, the total synthetic routes for several ETP alkaloids have been designed. In this review, we summarized several ETP alkaloids with anticancer properties with particular emphasis on their underlying mechanisms of action, structural modifications, and synthetic strategies, which will offer guidance to design and innovate potential anticancer drugs.

An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation.

Single-cell RNA sequencing (scRNA-seq) detects whole transcriptome signals for large amounts of individual cells and is powerful for determining cell-to-cell differences and investigating the functional characteristics of various cell types. scRNA-seq datasets are usually sparse and highly noisy. Many steps in the scRNA-seq analysis workflow, including reasonable gene selection, cell clustering and annotation, as well as discovering the underlying biological mechanisms from such datasets, are difficult. In this study, we proposed an scRNA-seq analysis method based on the latent Dirichlet allocation (LDA) model. The LDA model estimates a series of latent variables, i.e. putative functions (PFs), from the input raw cell-gene data. Thus, we incorporated the 'cell-function-gene' three-layer framework into scRNA-seq analysis, as this framework is capable of discovering latent and complex gene expression patterns via a built-in model approach and obtaining biologically meaningful results through a data-driven functional interpretation process. We compared our method with four classic methods on seven benchmark scRNA-seq datasets. The LDA-based method performed best in the cell clustering test in terms of both accuracy and purity. By analysing three complex public datasets, we demonstrated that our method could distinguish cell types with multiple levels of functional specialization, and precisely reconstruct cell development trajectories. Moreover, the LDA-based method accurately identified the representative PFs and the representative genes for the cell types/cell stages, enabling data-driven cell cluster annotation and functional interpretation. According to the literature, most of the previously reported marker/functionally relevant genes were recognized.

Identification of shared characteristics in tumor-infiltrating T cells across 15 cancers.

Tumor-infiltrating T cells are essential players in tumor immunotherapy. Great progress has been achieved in the investigation of T cell heterogeneity. However, little is well known about the shared characteristics of tumor-infiltrating T cells across cancers. In this study, we conduct a pan-cancer analysis of 349,799 T cells across 15 cancers. The results show that the same T cell types had similar expression patterns regulated by specific transcription factor (TF) regulons across cancers. Multiple T cell type transition paths were consistent in cancers. We found that TF regulons associated with CD8+ T cells transitioned to terminally differentiated effector memory (Temra) or exhausted (Tex) states were associated with patient clinical classification. We also observed universal activated cell-cell interaction pathways of tumor-infiltrating T cells in all cancers, some of which specifically mediated crosstalk in certain cell types. Moreover, consistent characteristics of TCRs in the aspect of variable and joining region genes were found across cancers. Overall, our study reveals common features of tumor-infiltrating T cells in different cancers and suggests future avenues for rational, targeted immunotherapies.

Ent-kauranes and ent-atisanes from Euphorbia wallichii and their anti-inflammatory activity.

Phytochemical investigation on the whole plant of Euphorbia wallichii led to the identification of twelve diterpenoids, including nine undescribed ones, in which wallkauranes A-E (1-5) were classified as ent-kaurane diterpenoids and wallatisanes A-D (6-9) were assigned as ent-atisane diterpenoids. The biological evaluation of these isolates against NO production was conducted in the LPS-induced RAW264.7 macrophage cells model, resulting in the identification of a series of potent NO inhibitors, with the most active wallkaurane A showing an IC50 value of 4.21 µM. The mechanistic study disclosed that wallkaurane A could inhibit pro-inflammatory cytokines generation such as TNF-α, IL-1ß, and IL-6, and decrease the expression of iNOS and COX-2. Wallkaurane A could regulate the NF-κB signaling pathways and the JAK2/STAT3 signaling pathway to suppress the inflammatory reaction in LPS-induced RAW264.7 cells. Meanwhile, wallkaurane A could also inhibit the JAK2/STAT3 signaling pathway, thereby suppressing apoptosis in LPS-induced RAW264.7 cells.

Low blood carotenoid status in dementia and mild cognitive impairment: A systematic review and meta-analysis.

BACKGROUND: Given their potent antioxidation properties, carotenoids play a role in delaying and preventing dementia and mild cognitive impairment (MCI). However, observational studies have found inconsistent results regarding the associations between blood carotenoid levels and the risk of dementia and MCI. We conducted this systematic review and meta-analysis to investigate the relationship between blood carotenoid levels and the risk of dementia and MCI. METHODS: A systematic search was performed in the Web of Science, PubMed, Embase, and Cochrane Library electronic databases to retrieve relevant English articles published from their inception until February 23, 2023. Study quality was assessed by the Newcastle-Ottawa scale. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were pooled using random-effect meta-analyses. Ultimately, 23 studies (n = 6610) involving 1422 patients with dementia, 435 patients with MCI, and 4753 controls were included. RESULTS: Our meta-analysis showed that patients with dementia had lower blood lycopene (SMD: -0.521; 95%CI: -0.741, -0.301), α-carotene (SMD: -0.489; 95%CI: -0.697, -0.281), ß-carotene (SMD: -0.476; 95%CI: -0.784, -0.168), lutein (SMD: -0.516; 95%CI: -0.753, -0.279), zeaxanthin (SMD: -0.571; 95%CI: -0.910, -0.232) and ß-cryptoxanthin (SMD: -0.617; 95%CI: -0.953, -0.281) than the controls. Our results indicated that blood carotenoid levels were significantly lower in patients with dementia than in controls, despite high heterogeneity across the studies. Owing to insufficient data, we did not observe a similar and stable relationship between blood carotenoid levels and MCI. CONCLUSIONS: Our meta-analysis indicated that lower blood carotenoid levels may be a risk factor for dementia and MCI.

Single-cell transcriptomics reveals the interaction between peripheral CD4+ CTLs and mesencephalic endothelial cells mediated by IFNG in Parkinson's disease.

Parkinson's disease (PD) is characterized by dopaminergic neurons degeneration in the substantia nigra pars compacta. Increasing evidence indicates that peripheral CD4+ T cells, a vital pathological component of PD, have been implicated in systemic inflammation activation, blood-brain barrier (BBB) dysfunction, central nervous system infiltration, and consequent neurons degeneration. However, there is no consensus on CD4+ T cell types' exact phenotypic characteristics in systemic inflammation and the mechanism of CD4+ T cells traffic into the BBB in patients with PD. In this study, we employed single-cell RNA sequencing (scRNA-seq) to elucidate the potential mechanism of T cells on the breakdown of BBB. The PD-associated Cytotoxic CD4+ T cells (CD4+ CTLs) were characterized by a significant increase in proportion as well as enhancement of interferon-gamma (IFNG) response and cell adhesion. Meanwhile, TBX21, IRF1 and NFATC2, identified as the key transcription factors in effector CD4+ T cells differentiation, induced overexpression of target genes-IFNG in CD4+ CTLs. Interestingly, endothelial cells (ECs) in PD patients were discovered to be more responsive to IFNG than other cell types of midbrain. Furthermore, the cell-cell communication analysis between CD4+ T cells and midbrain cells identified IFNG/IFNGR1 and SPP1/ITGB1 as the ligand-receptor pairs to mediate CD4+ CTLs' infiltration into the central nervous system (CNS) through the weakened ECs' tight junction. Together, these results suggested that PD-specific peripheral CD4+ CTLs might influence BBB function by migrating to mesencephalic endothelial cells (ECs) and activating the IFNG response in ECs.

Perceptions of Oncology Nurses Regarding Fertility Preservation and Providing Oncofertility Services for Men of Childbearing Age with Cancer.

This study investigated the knowledge, thoughts, and attitudes of oncology nurses in China regarding fertility preservation for male cancer patients of childbearing age, and for offering counseling or oncofertility services for the men in their care. Data was collected from 18 oncology nurses in Southwest China through voluntary self-report and in-depth interviews. The qualitative interview data were analyzed using a descriptive phenomenology method based on the lived experience of the nurses. The interviewees commonly reported 6 main concerns regarding fertility preservation (FP): their insufficient knowledge and inadequate nursing education; the importance of offering such services to cancer patients; legal vulnerability if FP information is withheld from patients; the role of the nurse in counseling; and barriers to discussing FP in practice. Nurses had a positive attitude toward FP, but most had no practical role in routinely informing male patients of their options, and the nurses believed that discussion of FP was outside their scope of practice. This study offers insight into the perceptions of oncology nurses in a developing country regarding the provision of FP services for adult male cancer patients. These results lead us to recommend that local fertility nurses should be given new training regarding FP. Furthermore, nurse-led clinics are desirable. Future research should focus on the effectiveness of nurse participation in FP counseling and referral, and how to improve the professional confidence of oncology nurses for addressing FP issues.

Prevalence and risk factors of self-reported financial toxicity in cancer survivors: A systematic review and meta-analyses.

BACKGROUND: Similar to the side effects of cancer treatment, financial toxicity (FT) can affect the quality of life of patients, which has attracted increasing attention in the field of oncology. Despite the fact that the estimated prevalence and risk factors of FT are widely reported, these results have not been synthesized. OBJECTIVES: This review is aimed to systematically assess the prevalence and risk factors of self-reported FT. DESIGN: Systematic review and meta-analyses. DATA SOURCES: A computer search of English literature was conducted using databases of PubMed, EMBASE, Web of Science, PsycINFO, and CINAHL, and reference lists of the qualified articles were also included between January 2010 and September 2021. Observational studies that reported the prevalence or risk factors of FT using subjective measures were included. METHODS: The systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The risk of bias was assessed by the NIH observational cohort and cross-sectional study quality assessment tool. The data were extracted by two reviewers and listed in a descriptive table for meta-analyses. RESULTS: In the 22 studies available for meta-analyses of pooled prevalence of FT, the result was estimated to be 45% (95% CI: 38% to 53%, I2 = 97.3%, P < 0.001) based on a random-effects model. The pooled analysis identified 9 potential risk factors of FT (7 in ß and 8 in OR): low income (OR = 2.48, 95% CI: 1.72 to 3.24, I2 = 3.1%, P < 0.001), greater annual OOP (ß = -4.26, 95% CI: -6.95 to -1.57, I2 = 0%, P = 0.002), younger age (OR = 2.05, 95% CI: 1.56 to 2.54, I2 = 0%, P < 0.001), no private insurance (OR = 1.69, 95% CI: 1.02 to 2.37, I2 = 0%, P < 0.001), unmarried (OR = 1.10, 95% CI: 0.95 to 1.25, I2 = 53,3%, P < 0.001), nonwhite (OR = 1.59, 95% CI: 1.33 to 1.85, I2 = 0%, P < 0.001), advanced cancer (ß = -4.74, 95% CI: -6.90 to -2.57, I2 = 0%, P < 0.001), unemployed (ß = -2.90, 95% CI: -5.71 to -0.63, I2 = 75,7%, P < 0.001), more recent diagnosis (OR = 1.31, 95% CI: 1.04 to 1.57, I2 = 0%, P < 0.001). CONCLUSION: This systematic review reported a pooled prevalence of self-reported FT of 45%. Low income, greater annual OOP (Out of pocket), younger age, unmarried, unemployed, nonwhite, no private insurance, advanced cancer, and more recent diagnosis constituted risk factors for self-reported FT. The research on risk factors for FT can provide a theoretical basis for medical staff to evaluate and intervene in the FT among cancer survivors.