Systematic Construction and Validation of a Novel Ferroptosis-Related Gene Model for Predicting Prognosis in Cervical Cancer

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

DERL2 (derlin 2) stabilizes BAG6 (BAG cochaperone 6) in chemotherapy resistance of cholangiocarcinoma

DERL2 (derlin 2) is a critical component of the endoplasmic reticulum quality control pathway system whose mutations play an important role in carcinogenesis, including cholangiocarcinoma (CHOL). However, its role and its underlying mechanism have yet to be elucidated. Herein, we revealed that DERL2 was highly expressed in CHOL and considered as an independent prognostic indicator for inferior survival in CHOL. DERL2 ectopically expressed in CHOL cells promoted cell proliferation and colony formation rates, and depleting DERL2 in CHOL cells curbed tumor growth in vitro and in vivo. More interestingly, the knockout of DERL2 augmented the growth-inhibitory effect of gemcitabine chemotherapy on CHOL cells by inducing cell apoptosis. Mechanistically, we discovered that DERL2 interacted with BAG6 (BAG cochaperone 6), thereby extending its half-life and reinforcing the oncogenic role of BAG6 in CHOL progression.

Identification of ferroptosis-related molecular subtypes and a methylation-related ferroptosis gene prognostic signature in cervical squamous cell carcinoma

PURPOSE

We aimed to investigate the molecular characteristics of cervical squamous cell carcinoma (CESC) by analyzing ferroptosis-related gene (FRG) expression data to predict prognosis.

METHODS

Gene expression and clinicopathological data of patients with CESC were collected from the Cancer Genome Atlas and the Genotype-Tissue Expression databases. Using Cox regression analysis, we identified 21 FRGs associated with prognosis. Cluster analysis categorized patients into subgroups based on these genes and compared their clinicopathological, biological, and immune infiltration features. FRG methylation levels were examined, and a risk model based on such FRG methylation levels was constructed using LASSO and Cox regression analyses. The model's predictive capacity was validated, and the relationships between the risk score and immune infiltration, tumor microenvironment, and drug sensitivity were explored. FRG methylation in CESC tissues was validated by immunohistochemistry.

RESULTS

We identified 21 FRGs associated with CESC prognosis. Patients were stratified into two subtypes based on these genes, they showed differences in prognosis, immune cell types, and immune checkpoint expression. A three-gene risk score (including AQP3, MGST1, and TFRC) was generated, and the low-risk group showed better overall survival. The high-risk and low-risk groups differed in terms of immune infiltration, gene mutations, and drug sensitivity. Experimental validation confirmed the upregulation of AQP3 and TFRC, whereas MGST1 expression was not significantly altered in CESC tissues compared with that in normal cervical tissues.

CONCLUSION

This study highlights the potential role of FRG methylation in predicting CESC prognosis and provides a personalized assessment of immune responses in patients with CESC.

RNF130 protects against pulmonary fibrosis through suppressing aerobic glycolysis by mediating c-myc ubiquitination

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal disease,characterized by an excessive accumulation of extracellular matrix (ECM) proteins in response to chronic lung injury. Current evidence suggests that metabolic reprogramming is always accompanied by myofibroblast activation in IPFof whichthe underlying mechanisms remain unclear. Ring finger protein 130 (RNF130), was demonstrated involved in multiple diseases. However, whether RNF130 plays a critical role in the pathogenesis of IPF needs to be clarified.

METHODS

We first investigated the expression of RNF130 in pulmonary fibrosis in vivo and in vitro. We then observed the effect and explored the molecular mechanism of RNF130 on the transition of fibroblast to myofibroblast and aerobic glycolysis. Further, we assessed the effects of adeno-associated virus (AAV)-induced RNF130 overexpression in the pulmonary fibrosis model, conducting pulmonary function, assessment of collagen depositionusing the hydroxyproline assay, and biochemical and histopathological analyses.

RESULTS

We found that RNF130 was down-regulated in lung tissues of mice with bleomycin-induced pulmonary fibrosis and lung fibroblasts treated with transforming growth factor-β1 (TGF-β1). Then we demonstrated that RNF130 inhibitedthe transition of fibroblast to myofibroblast by suppressing aerobic glycolysis. Mechanistically, we revealed that RNF130 promotedc-myc ubiquitination and degradation, while c-myc overexpression reverses the inhibitory effects of RNF130. Importantly, pulmonary function, collagen deposition and fibroblast differentiation were significantly alleviated in adeno-associated virus serotype (AAV)6-RNF130 treated mice, which further validated the contribution of RNF130/c-myc signaling axis in pulmonary fibrosis pathological process.

CONCLUSIONS

In summary, RNF130 participates in the pathogenesis of pulmonary fibrosis by inhibiting the transition of fibroblast to myofibroblast and aerobic glycolysis through promoting c-myc ubiquitination and degradation. Targeting RNF130-c-myc axismightrepresent a promising strategy to alleviate the progression of IPF.

Ferroptosis-related genes in cervical cancer as biomarkers for predicting the prognosis of gynecological tumors

Background: Ferroptosis has been identified as a potent predictor of cancer prognosis. Currently, cervical cancer ranks among the most prevalent malignant tumors in women. Enhancing the prognosis for patients experiencing metastasis or recurrence is of critical importance. Consequently, investigating the potential of ferroptosis-related genes (FRGs) as prognostic biomarkers for cervical cancer patients is essential. Methods: In this study, 52 FRGs were obtained from the GSE9750, GSE7410, GSE63514, and FerrDb databases. Six genes possessing prognostic characteristics were identified: JUN, TSC22D3, SLC11A2, DDIT4, DUOX1, and HELLS. The multivariate Cox regression analysis was employed to establish and validate the prognostic model, while simultaneously performing a correlation analysis of the immune microenvironment. Results: The prediction model was validated using TCGA-CESC and GSE44001 datasets. Furthermore, the prognostic model was validated in endometrial cancer and ovarian serous cystadenocarcinoma cases. KM curves revealed significant differences in OS between high-risk and low-risk groups. ROC curves demonstrated the stability and accuracy of the prognostic model established in this study. Concurrently, the research identified a higher proportion of immune cells in patients within the low-risk group. Additionally, the expression of immune checkpoints (TIGIT, CTLA4, BTLA, CD27, and CD28) was elevated in the low-risk group. Ultimately, 4 FRGs in cervical cancer were corroborated through qRT-PCR. Conclusion: The FRGs prognostic model for cervical cancer not only exhibits robust stability and accuracy in predicting the prognosis of cervical cancer patients but also demonstrates considerable prognostic value in other gynecological tumors.

From past to future: Bibliometric analysis of global research productivity on nomogram (2000-2021)

Background

Nomogram, a visual clinical predictive model, provides a scientific basis for clinical decision making. Herein, we investigated 20 years of nomogram research responses, focusing on current and future trends and analytical challenges.

Methods

We mined data of scientific literature from the Core Collection of Web of Science, searching for the original articles with title "Nomogram^*/Parton Table^*/Parton Nomogram^*", published within January 1st, 2000 to December 30th, 2021. Data records were validated using HistCite Version and analyzed with a transformable statistical method, the Bibliometrix 3.0 package of R Studio.

Results

In total, 4,176 original articles written by 19,158 authors were included from 915 sources. Annually, Nomogram publications are continually produced, which have rapidly grown since 2018. China published the most articles; however, its total citations ranked second after the United States. Both total citations and average article citations in the United States rank first globally, and a high degree of cooperation exists between countries. Frontiers in Oncology published the most papers (238); this number has grown rapidly since 2019. Journal of Urology had the highest H-index, with an average increase in publications over the past 20 years. Most research topics were tumor-related, among which tumor risk prediction and prognostic evaluation were the main contents. Research on prognostic assessment is more published and advanced, while risk prediction and diagnosis have good developmental prospects. Furthermore, nomogram of the urinary system has been highly developed. Following advancements in nomogram modeling, it has recently been applied to non-oncological subjects.

Conclusion

This bibliometric analysis provides a comprehensive overview of the current nomogram status, which could enable better understanding of its development over the years, and provide global researchers a comprehensive analysis and structured information to help identify hot spots and gaps in future research.