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

Development of a m6A- and ferroptosis-related LncRNA signature for forecasting prognosis and treatment response in cervical cancer

BACKGROUND

N6-methyladenosine (m6A) and ferroptosis are involved in the development and prognosis of various cancers via long noncoding RNAs (lncRNAs). This study aimed to investigate the cervical cancer subtypes based on m6A-and ferroptosis-related lncRNAs (mfrlncRNAs) and to construct a mfrlncRNA signature to predict cervical cancer prognosis and treatment response.

METHODS

mfrlncRNA-related cervical cancer subtypes were identified based on public datasets, and their differences in terms of prognosis, immune cell infiltration, and biological mechanisms were compared. Moreover, prognosis-related mfrlncRNAs were identified to construct a prognostic signature. A nomogram was constructed based on the independent prognostic factors. Immune characteristics, immunotherapy response predictions, and drug sensitivity analyses were performed for both risk groups. Furthermore, quantitative PCR was performed to validate the differential expression of the signature mfrlncRNAs in clinical samples.

RESULTS

In total, 549 differentially expressed mfrlncRNAs were identified between cervical cancer and normal samples. Two mfrlncRNA-related cervical cancer subtypes that exhibited distinct prognoses, immune characteristics, and biological mechanisms were identified. A prognostic signature was developed using six prognostic mfrlncRNAs: AC016065.1, AC096992.2, AC119427.1, AC133644.1, AL121944.1, and FOXD1_AS1. This prognostic signature exhibited high performance in predicting the prognosis of cervical cancer. Moreover, RiskScore and stage were identified as independent prognostic factors, and a nomogram was constructed to accurately forecast overall survival. Furthermore, patients in the low-risk group had a more active immunotherapy response and were more sensitive to chemotherapeutic drugs such as imatinib. Upregulated expression of AC119427.1, AC133644.1, AL121944.1, and FOXD1_AS1 was observed in the tumor samples.

CONCLUSIONS

The six-mfrlncRNA signature is a new biomarker for forecasting prognosis and treatment response in cervical cancer.

Therapeutic implications of endoplasmic reticulum stress gene CCL3 in cervical squamous cell carcinoma

This study investigated ERS-related gene expressions in CESC, identifying two molecular subtypes, P1 and P2, and constructing a precise prognostic model based on these subtypes. TCGA's whole-genome expression profiles were used to recognize these subtypes through the ConsensusClusterPlus method, further refining prognostic models with univariate and Lasso Cox regression analyses validated by the GSE39001 dataset. The study analyzed the expression distribution of ERS marker genes within T cell subgroups using scRNA-seq data (GSE168652), highlighting T cell diversity. The critical role of the CCL3 gene in prognostic models was examined explicitly in CD8 + T cells from healthy individuals and CESC patients. Elevated CCL3 levels were observed in patients' CD8 + T cells compared to healthy controls. Functional experiments involving CCL3 knockdown and overexpression in HeLa and SiHa CESC cell lines were conducted to investigate its impact on cell proliferation, migration, and invasion. These findings were subsequently validated in a nude mouse model. The results demonstrated that suppressing CCL3 inhibited cell proliferation, migration, and invasion significantly, while its overexpression promoted these processes. In the mouse model, CCL3 silencing reduced tumor growth and decreased Ki-67 labeling within the tumor tissues, indicating the therapeutic potential of targeting CCL3 in CESC treatment, possibly through CD8 + T cell regulation. This study contributes new prognostic assessment tools and personalized treatment options for CESC patients, paving the way for more targeted therapies in CESC by discovering the CCL3 gene, presenting significant clinical implications.

TIPE Inhibits Ferroptosis in Colorectal Cancer Cells by Regulating MGST1/ALOX5

TIPE is a protein highly expressed in various cancers that promotes ferroptosis in colorectal cancer cells. Ferroptosis is a nonapoptotic cell death caused by lipid peroxidation, and microsomal glutathione transferase 1 (MGST1) is a critical enzyme that resists lipid peroxidation. This study explored how TIPE regulates MGST1 expression to inhibit ferroptosis and promote colorectal cancer proliferation. TIPE was highly expressed in colorectal cancer tissues and positively correlated with the proliferation of human colorectal cancer cells. We measured levels of reactive oxygen species and lipid reactive oxygen species in colorectal cancer cells with differential expression of TIPE and detected ferroptosis using transmission electron microscopy. Bioinformatics analysis revealed a positive correlation of expression patterns between TIPE and MGST1 in colorectal cancer. TIPE regulated the expression of MGST1 by activating the phosphorylation of ERK1/2. Coimmunoprecipitation revealed binding between MGST1 and ALOX5. This binding inhibited the phosphorylation of ALOX5, inhibiting ferroptosis and promoting the proliferation of colorectal cancer cells. A tumor formation experiment in nude mice supported our findings that TIPE regulates the proliferation of colorectal cancer by regulating ferroptosis. Implications: TIPE inhibits colorectal cancer ferroptosis via an MGST1-ALOX5 interaction to promote colorectal cancer proliferation. These findings suggest future colorectal cancer treatment strategies.

Cross-talk between cuproptosis and ferroptosis to identify immune landscape in cervical cancer for mRNA vaccines development

Messenger RNA (mRNA)-based vaccines present a promising avenue for cancer immunotherapy; however, their application in cervical cancer remains unexplored. This study investigated the interplay between the regulated cell death pathways of cuproptosis and ferroptosis to advance the development of mRNA vaccines for cervical cancer. We identified key cuproptosis-related and ferroptosis-related genes (CFRGs) from public mRNA profiles and determined their prognostic significance, mutation frequencies, and effect on the immune landscape. Our analysis revealed two distinct subtypes of cervical cancer associated with CFRGs, with differences in prognosis and immune characteristics. Using LASSO, XGBoost, and SVM-RFE methods, we established a 4-gene prognostic signature (TSC22D3, SQLE, ZNF419, and TFRC) to stratify patients based on their risk and determine its correlation with immune microenvironment, mutation profiles, and treatment responses. RT-qPCR validation confirmed the differential expression of these genes in clinical samples. Our findings identify TSC22D3, SQLE, ZNF419, and TFRC as candidate targets for mRNA vaccine development and offer a potential prognostic tool for personalized cervical cancer treatment.

The recent advancements of ferroptosis of gynecological cancer

Ovarian, endometrial, and cervical cancer are the most common types of gynecologic tumor in women. Surgery, combined with radiotherapy and chemotherapy, is commonly used to treat these tumors. Unfortunately, difficulties in early diagnosis and acquired drug resistance have resulted in poor outcomes for most patients. Ferroptosis is a form of regulated cell death that depends on iron and is characterized by iron accumulation, reactive oxygen species production, and lipid peroxidation. The strong association between ferroptosis and many diseases, especially tumor diseases, has been confirmed by numerous studies. Many studies have demonstrated that ferroptosis is involved in initiating, progressing and metastasizing gynecologic tumors. This review summarizes the pathogenesis of ferroptosis and its association with the development, treatment, and prognosis of gynecologic tumors, and further explore the potential utility of ferroptosis in treating gynecologic tumors.

Identification of novel biomarkers based on lipid metabolism-related molecular subtypes for moderately severe and severe acute pancreatitis

BACKGROUND

Acute pancreatitis (AP) is an unpredictable and potentially fatal disorder. A derailed or unbalanced immune response may be the root of the disease's severe course. Disorders of lipid metabolism are highly correlated with the occurrence and severity of AP. We aimed to characterize the contribution and immunological characteristics of lipid metabolism-related genes (LMRGs) in non-mild acute pancreatitis (NMAP) and identify a robust subtype and biomarker for NMAP.

METHODS

The expression mode of LMRGs and immune characteristics in NMAP were examined. Then LMRG-derived subtypes were identified using consensus clustering. The weighted gene co-expression network analysis (WGCNA) was utilized to determine hub genes and perform functional enrichment analyses. Multiple machine learning methods were used to build the diagnostic model for NMAP patients. To validate the predictive effectiveness, nomograms, receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) were used. Using gene set variation analysis (GSVA) and single-cell analysis to study the biological roles of model genes.

RESULTS

Dysregulated LMRGs and immunological responses were identified between NMAP and normal individuals. NMAP individuals were divided into two LMRG-related subtypes with significant differences in biological function. The cluster-specific genes are primarily engaged in the regulation of defense response, T cell activation, and positive regulation of cytokine production. Moreover, we constructed a two-gene prediction model with good performance. The expression of CARD16 and MSGT1 was significantly increased in NMAP samples and positively correlated with neutrophil and mast cell infiltration. GSVA results showed that they are mainly upregulated in the T cell receptor complex, immunoglobulin complex circulating, and some immune-related routes. Single-cell analysis indicated that CARD16 was mainly distributed in mixed immune cells and macrophages, and MGST1 was mainly distributed in exocrine glandular cells.

CONCLUSIONS

This study presents a novel approach to categorizing NMAP into different clusters based on LMRGs and developing a reliable two-gene biomarker for NMAP.