Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

Dong, Xinyi; Zhou, Mi; Li, Xinyu; Huang, Huijing; Sun, Yun

doi:10.3389/fgene.2023.1108805

Cited by 4 publications

(4 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Over Representation Analysis indicates that the package identified module M6 (Figure 5E). The top 13 genes were linked with two primary mechanisms, inflammation and immune regulation and DNA repair and genome stability mechanisms. Inflammation and immune regulation: Genes including HMGB3, IGBP1, LIF, P2RY6 and ESR1 are implicated in inflammatory responses and immune regulation 60–63 . These are potentially associated with inflammatory skin conditions such as eczema and psoriasis. DNA repair and genome stability: Genes such as BRCA1, DHX15, PRKDC and CBL participate in DNA repair and the maintenance of genome stability.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets

Liu,

Lu,

Qiu

et al. 2023

International Wound Journal

View full text Add to dashboard Cite

Pathological scarring resulting from traumas and wounds, such as hypertrophic scars and keloids, pose significant aesthetic, functional and psychological challenges. This study provides a comprehensive transcriptomic analysis of these conditions, aiming to illuminate underlying molecular mechanisms and potential therapeutic targets. We employed a co‐expression and module analysis tool to identify significant gene clusters associated with distinct pathophysiological processes and mechanisms, notably lipid metabolism, sebum production, cellular energy metabolism and skin barrier function. This examination yielded critical insights into several skin conditions including folliculitis, skin fibrosis, fibrosarcoma and congenital ichthyosis. Particular attention was paid to Module Cluster (MCluster) 3, encompassing genes like BLK, TRPV1 and GABRD, all displaying high expression and potential implications in immune modulation. Preliminary immunohistochemistry validation supported these findings, showing elevated expression of these genes in non‐fibrotic samples rich in immune activity. The complex interplay of different cell types in scar formation, such as fibroblasts, myofibroblasts, keratinocytes and mast cells, was also explored, revealing promising therapeutic strategies. This study underscores the promise of targeted gene therapy for pathological scars, paving the way for more personalised therapeutic approaches. The results necessitate further research to fully ascertain the roles of these identified genes and pathways in skin disease pathogenesis and potential therapeutics. Nonetheless, our work forms a strong foundation for a new era of personalised medicine for patients suffering from pathological scarring.

show abstract

Section: Resultsmentioning

confidence: 99%

“…• Inflammation and immune regulation: Genes including HMGB3, IGBP1, LIF, P2RY6 and ESR1 are implicated in inflammatory responses and immune regulation. [60][61][62][63] These are potentially associated with inflammatory skin conditions such as eczema and psoriasis.…”

Section: Mclustermentioning

confidence: 99%

Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets

Liu,

Lu,

Qiu

et al. 2023

International Wound Journal

View full text Add to dashboard Cite

show abstract

“…Compared to previous studies (Wang and Liu, 2020;Dong et al, 2023;Lai et al, 2023), we first used three comprehensive microarray datasets GSE58144 (Koot et al, 2016), GSE103465 (Guo et al, 2018), and GSE111974 (Bastu et al, 2019) comprising 99 RIF and 70 normal endometrial tissues, and both enrichment analysis and WGCNA were conducted to distinguish hub genes associated with RIF. The WGCNA has made the greatest contribution to finding association patterns among genes across samples and interpreting the direct biological role of gene network modules, which makes our results more effective and reliable.…”

Section: Discussionmentioning

confidence: 99%

Analysis of weighted gene co-expression networks and clinical validation identify hub genes and immune cell infiltration in the endometrial cells of patients with recurrent implantation failure

Liu,

Lai,

et al. 2024

Front. Genet.

View full text Add to dashboard Cite

Background:About 10% of individuals undergoing in vitro fertilization encounter recurrent implantation failure (RIF), which represents a worldwide social and economic concern. Nevertheless, the critical genes and genetic mechanisms underlying RIF are largely unknown.Methods:We first obtained three comprehensive microarray datasets “GSE58144, GSE103465 and GSE111974”. The differentially expressed genes (DEGs) evaluation, enrichment analysis, as well as efficient weighted gene co-expression network analysis (WGCNA), were employed for distinguishing RIF-linked hub genes, which were tested by RT-qPCR in our 30 independent samples. Next, we studied the topography of infiltration of 22 immune cell subpopulations and the association between hub genes and immune cells in RIF using the CIBERSORT algorithm. Finally, a novel ridge plot was utilized to exhibit the potential function of core genes.Results:The enrichment of GO/KEGG pathways reveals that Herpes simplex virus 1 infection and Salmonella infection may have an important role in RIF. After WGCNA, the intersected genes with the previous DEGs were obtained using both variance and association. Notably, the subsequent nine hub genes were finally selected: ACTL6A, BECN1, SNRPD1, POLR1B, GSK3B, PPP2CA, RBBP7, PLK4, and RFC4, based on the PPI network and three different algorithms, whose expression patterns were also verified by RT-qPCR. With in-depth analysis, we speculated that key genes mentioned above might be involved in the RIF through disturbing endometrial microflora homeostasis, impairing autophagy, and inhibiting the proliferation of endometrium. Furthermore, the current study revealed the aberrant immune infiltration patterns and emphasized that uterine NK cells (uNK) and CD4+ T cells were substantially altered in RIF endometrium. Finally, the ridge plot displayed a clear and crucial association between hub genes and other genes and key pathways.Conclusion:We first utilized WGCNA to identify the most potential nine hub genes which might be associated with RIF. Meanwhile, this study offers insights into the landscape of immune infiltration status to reveal the underlying immune pathogenesis of RIF. This may be a direction for the next study of RIF etiology. Further studies would be required to investigate the involved mechanisms.

show abstract

“…The R software “ESTIMATE” package was used to analyze the immune scores and stromal scores in different clusters to explore the infiltration of immune cells and stromal cells in TME. Furthermore, the infiltration data of immune cell in HCC were obtained from the online website CIBERSORT ( Liu et al, 2023 ) ( ), and the R “ggpubr” and “limma” packages ( Dong et al, 2023 ) were used to visualize the differences in clusters.…”

Section: Methodsmentioning

confidence: 99%

Novel application of the ferroptosis-related genes risk model associated with disulfidptosis in hepatocellular carcinoma prognosis and immune infiltration

Wei,

Wang,

Chen

et al. 2024

PeerJ

View full text Add to dashboard Cite

Hepatocellular carcinoma (HCC) stands as the prevailing manifestation of primary liver cancer and continues to pose a formidable challenge to human well-being and longevity, owing to its elevated incidence and mortality rates. Nevertheless, the quest for reliable predictive biomarkers for HCC remains ongoing. Recent research has demonstrated a close correlation between ferroptosis and disulfidptosis, two cellular processes, and cancer prognosis, suggesting their potential as predictive factors for HCC. In this study, we employed a combination of bioinformatics algorithms and machine learning techniques, leveraging RNA sequencing data, mutation profiles, and clinical data from HCC samples in The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) databases, to develop a risk prognosis model based on genes associated with ferroptosis and disulfidptosis. We conducted an unsupervised clustering analysis, calculating a risk score (RS) to predict the prognosis of HCC using these genes. Clustering analysis revealed two distinct HCC clusters, each characterized by significantly different prognostic and immune features. The median RS stratified HCC samples in the TCGA, GEO, and ICGC cohorts into high-and low-risk groups. Importantly, RS emerged as an independent prognostic factor in all three cohorts, with the high-risk group demonstrating poorer prognosis and a more active immunosuppressive microenvironment. Additionally, the high-risk group exhibited higher expression levels of tumor mutation burden (TMB), immune checkpoints (ICs), and human leukocyte antigen (HLA), suggesting a heightened responsiveness to immunotherapy. A cancer stem cell infiltration analysis revealed a higher similarity between tumor cells and stem cells in the high-risk group. Furthermore, drug sensitivity analysis highlighted significant differences in response to antitumor drugs between the two risk groups. In summary, our risk prognostic model, constructed based on ferroptosis-related genes associated with disulfidptosis, effectively predicts HCC prognosis. These findings hold potential implications for patient stratification and clinical decision-making, offering valuable theoretical insights in this field.

show abstract

Gene profiling reveals the role of inflammation, abnormal uterine muscle contraction and vascularity in recurrent implantation failure

Cited by 4 publications

References 74 publications

Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets

Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets

Analysis of weighted gene co-expression networks and clinical validation identify hub genes and immune cell infiltration in the endometrial cells of patients with recurrent implantation failure

Novel application of the ferroptosis-related genes risk model associated with disulfidptosis in hepatocellular carcinoma prognosis and immune infiltration

Contact Info

Product

Resources

About