Analysis of a new therapeutic target and construction of a prognostic model for breast cancer based on ferroptosis genes

Identification of RUVBL2 as a novel biomarker to predict the prognosis and drug sensitivity in multiple myeloma based on ferroptosis genes

BACKGROUND

Multiple myeloma (MM) is a hematological malignancy with the proliferation of malignant plasma cells. Numerous studies have highlighted the critical role of ferroptosis in MM. However, how to use ferroptosis-related genes (FRGs) for prognostic prediction and treatment guidance in MM remains unknown.

METHODS

By analysis of GEO databases, the prognostic gene was identified and a therapeutic strategy for MM patients based on FRGs was explored. A total of 12 FRGs were identified, utilizing the STRING database and Cytoscape software, and the PPI networks were constructed to identify hub genes and further functional enrichment analyses. Based on the aforementioned data, this study analyzed the expression of RUVBL2 in MM patients by qRT-PCR and Western blotting. To validate the functional role of RUVBL2 in the MM cells, cellular experiments were ultimately conducted.

RESULTS

The analysis highlighted six hub genes, including TP53, MCM5, TLR4, RUVBL2, GCLM and ITGA6, and functional enrichment analyses indicating enrichment in DNA replication, regulation of apoptotic signaling pathway and PI3K/AKT signaling pathway. Prognostic analysis indicated that TP53, RUVBL2, and MCM5 are associated with MM prognosis, with RUVBL2 displaying a notable area under the curve (AUC) of 0.823 in ROC analysis. The study first determined that RUVBL2 is highly expressed in MM, siRUVBL2-mediated deletion of RUVBL2 inhibited proliferation, promoted apoptosis and increased the sensitivity of BTZ in MM cells, and also overcame BTZ resistance in CD138+ primary cells from MM patients.

CONCLUSIONS

Our study first suggested that RUVBL2 may be regarded as potential therapeutic targets and prognostic value in MM.

A Breast Cancer Prognostic Model Based on Folic Acid Metabolism-Related Genes to Reveal the Immune Landscape

Breast cancer (BC) threatens women's health, and the prognosis is dismal. Folic acid metabolism affects cancer prognosis, but research on folic acid metabolism-related genes (FMRs) in BC is scarce. We used TCGA-BRCA as the training set and GSE21653 as the validation set. Five FMRs (PLAT, SERPINA3, IFNG, SLC19A1, NFKB2) were screened via univariate and LASSO Cox regression analyses, and a prognostic model was built based on multivariate Cox regression analysis. The model showed excellent predictive performance. Differentially expressed genes in high- and low-risk groups were enriched in steroid hormone biosynthesis and neuroactive ligand-receptor interaction pathways. The low-risk group exhibited higher immune cell infiltration and better immunotherapy response. AM-5992 and 5-fluorodeoxyuridine 10mer may be potential BC drugs. This FMR-based model can accurately predict BC prognosis, offering a clinical reference.

Mitochondrial metabolism-related features guiding precision subtyping and prognosis in breast cancer, revealing FADS2 as a novel therapeutic target

BACKGROUND

Breast cancer is one of the most prevalent malignant tumors in women. Mitochondria, essential for cellular function, have altered metabolic activity in cancer cells, influencing tumor regulation and clinical outcomes. The connection between mitochondrial metabolism-related genes and breast cancer prognosis remains underexplored. This study aims to investigate the role of these genes in breast cancer by constructing risk models.

METHODS

Breast cancer transcriptome data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and mitochondrial gene data were sourced from the MitoCarta3.01 database. Clustering analysis was conducted using the "ConsensusClusterPlus" package, followed by Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A prognostic model was built using Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms. Immune cell infiltration levels were assessed via CIBERSORT and MCPcounter algorithms. Validation of key gene expression was performed on breast cancer tissue specimens and cell models to explore their biological functions in breast cancer cells.

RESULTS

The LASSO regression analysis of the TCGA BRCA dataset identified four prognosis-related mitochondrial metabolism genes: MYH11, LTF, FADS2, and PSPHP1. Validation using the GEO dataset confirmed that patients with high-risk scores (based on these four genes) had shorter overall survival compared to those with lower risk scores. Immunological analysis revealed that high-risk patients were less responsive to immunotherapy but more sensitive to conventional chemotherapies. This suggests that combining chemotherapy with immunotherapy might enhance T cell-based treatments. Univariate and multivariate Cox regression confirmed that the mitochondrial gene model was an independent predictor of overall survival, and a nomogram was developed to predict patient prognosis. Tissue validation showed consistent expression patterns with bioinformatic predictions. Functional assays confirmed that FADS2 was highly expressed in breast cancer cells, and its knockout significantly reduced cell invasion, migration, and colony formation.

CONCLUSION

This study reveals that mitochondrial metabolism-related genes are closely associated with breast cancer progression, clinical outcomes, and genetic alterations. The findings may offer new avenues for treatment strategies, early intervention, and prognosis prediction in breast cancer.

Hedyotis diffusa injection modulates the ferroptosis in bladder cancer via CAV1/JUN/VEGFA

Hedyotis diffusa Willd. (HDW), a traditional Chinese medicinal plant, exhibits a variety of pharmacological effects and has anticancer potential for a wide range of cancer types; Ferroptosis is a non-apoptosis-regulated cell death induced by iron accumulation and subsequent lipid peroxidation; and there is currently an increasing interest in the therapeutic role of ferroptosis in cancer. However, the effects of HDW on bladder cancer and its underlying molecular mechanisms remain largely unknown. In this study, a combination of in vivo and in vitro experiments, network pharmacology and data mining methods were used to investigate the effects of HDW on BLCA. The results showed that HDW exerted its anticancer activity by inducing ferroptosis in bladder cancer cells. Subsequently, we demonstrated for the first time that HDW induced ferroptosis in vitro and in vivo. To further explore the possible targets of HDW-induced ferroptosis in bladder cancer, we performed network pharmacological analyses, transcriptomic analyses, and single-cell analyses; through integrative analyses, we identified three key pivotal genes associated with iron death, CAV1, VEGFA, and JUN.Mechanistically, we showed that CAV1, VEGFA and JUN are key determinants of HDW-induced ferroptosis in BLCA. Knockdown of target genes altered the anticancer effects of HDW in 5637 and T24 cells. In conclusion, our data show for the first time that HDW exerts its anticancer effects on BLCA through CAV1, VEGFA and JUN gene-induced ferroptosis. This is expected to provide a promising compound for bladder cancer therapy.

The construction of a breast cancer prognostic model by combining genes related to hypoxia and endoplasmic reticulum stress

Breast cancer (BC) is a malignant tumor that occurs in breast tissue. This project aims to predict the prognosis of BC patients using genes related to hypoxia and endoplasmic reticulum stress (ERS). RNA-seq and clinical data for BC were downloaded from TCGA and GEO databases. Hypoxia and ERS-related genes were collected from the Genecards database. Univariate/multivariate Cox regression and Lasso regression analyses were used to screen genes and construct prognostic models. Patients were divided into high-risk (HR) and low-risk (LR) groups based on risk scores. The CIBERSORT algorithm was used to analyze differences in immune infiltration between the two groups. The mutations of the two groups were analyzed statistically. The CellMiner database was used for drug prediction and the TISCH database for single-cell sequencing analysis. We screened 8 feature genes to construct a prognostic model. Patients in the HR group had a remarkably worse prognosis. TP53 exhibited a higher mutation frequency in the HR group. CIBERSORT analysis uncovered a remarkable increase in the infiltration levels of Macrophages M0 and Tregs in cancer patients and HR patients. Drug sensitivity prediction demonstrated that the expression of IVL was greatly negatively linked with the sensitivity of COLCHICINE. PTGS2 had a remarkably negative correlation with the Vincristine sensitivity. The prognostic model based on 8 hypoxia and ERS-related genes can predict the survival, immune status, and potential drugs of BC patients, bringing a new perspective on individualized treatment.

Targeting the initiator to activate both ferroptosis and cuproptosis for breast cancer treatment: progress and possibility for clinical application

Breast cancer is the most commonly diagnosed cancer worldwide. Metal metabolism is pivotal for regulating cell fate and drug sensitivity in breast cancer. Iron and copper are essential metal ions critical for maintaining cellular function. The accumulation of iron and copper ions triggers distinct cell death pathways, known as ferroptosis and cuproptosis, respectively. Ferroptosis is characterized by iron-dependent lipid peroxidation, while cuproptosis involves copper-induced oxidative stress. They are increasingly recognized as promising targets for the development of anticancer drugs. Recently, compelling evidence demonstrated that the interplay between ferroptosis and cuproptosis plays a crucial role in regulating breast cancer progression. This review elucidates the converging pathways of ferroptosis and cuproptosis in breast cancer. Moreover, we examined the value of genes associated with ferroptosis and cuproptosis in the clinical diagnosis and treatment of breast cancer, mainly outlining the potential for a co-targeting approach. Lastly, we delve into the current challenges and limitations of this strategy. In general, this review offers an overview of the interaction between ferroptosis and cuproptosis in breast cancer, offering valuable perspectives for further research and clinical treatment.

Integrated analysis of ferroptosis and stemness based on single-cell and bulk RNA-sequencing data provide insights into the prognosis and treatment of esophageal carcinoma

BACKGROUND

Cancer stem cells (CSCs) play a significant role in the recurrence and drug resistance of esophageal carcinoma (ESCA). Ferroptosis is a promising anticancer therapeutic strategy that effectively targets CSCs exhibiting high tumorigenicity and treatment resistance. However, there is a lack of research on the combined role of ferroptosis-related genes (FRGs) and stemness signature in the prognosis of ESCA.

METHODS

The cellular compositions were characterized using single-cell RNA sequencing (scRNA-seq) data from 18 untreated ESCA samples. 50 ferroptosis-related stemness genes (FRSGs) were identified by integrating FRGs with stemness-related genes (SRGs), and then the cells were grouped by AUCell analysis. Next, functional enrichment, intercellular communication, and trajectory analyses were performed to characterize the different groups of cells. Subsequently, the stem-ferr-index was calculated using machine learning algorithms based on the expression profiles of the identified risk genes. Additionally, therapeutic drugs were predicted by analyzing the GDSC2 database. Finally, the expression and functional roles of the identified marker genes were validated through in vitro experiments.

RESULTS

The analysis of scRNA-seq data demonstrates the diversity and cellular heterogeneity of ESCA. Then, we identified 50 FRSGs and classified cells into high or low ferroptosis score stemness cells accordingly. Functional enrichment analysis conducted on the differentially up-regulated genes between these groups revealed predominant enrichment in pathways associated with intercellular communication and cell differentiation. Subsequently, we identified 9 risk genes and developed a prognostic signature, termed stem_ferr_index, based on these identified risk genes. We found that the stem-ferr-index was correlated with the clinical characteristics of patients, and patients with high stem-ferr-index had poor prognosis. Furthermore, we identified four drugs (Navitoclax, Foretinib, Axitinib, and Talazoparib) with potential efficacy targeting patients with a high stem_ferr_index. Additionally, we delineated two marker genes (STMN1 and SLC2A1). Particularly noteworthy, SLC2A1 exhibited elevated expression levels in ESCA tissues and cells. We provided evidence suggesting that SLC2A1 could influence the migration, invasion, and stemness of ESCA cells, and it was associated with sensitivity to Foretinib.

CONCLUSION

This study constructed a novel ferroptosis-related stemness signature, identified two marker genes for ESCA, and provided valuable insights for developing more effective therapeutic targets targeting ESCA CSCs in the future.

ChaC1 upregulation reflects poor prognosis in a variety of cancers: analysis of the major missense SNPs of ChaC1 as an aid to refining prognosis

The ChaC1 enzyme that catalyzes cytosolic glutathione degradation is highly upregulated in several cancers. In a systematic review of gene signature panels for cancer prognosis based on oxidative stress and ferroptosis genes, we observed that ChaC1 was found in panels in a wide variety of different cancers, with the upregulation correlating with poor prognosis. Since SNPs can have an impact on functionality and prognosis, ChaC1 SNPs from various databases were also investigated. Six frequently observed missense SNPs were chosen for reconstruction, and their functionality was evaluated. Three out of six SNPs resulted in either a partial or complete loss of ChaC1 function, and these SNPs had the changes R72Q, A156V, and G173S in their proteins. This study highlights the importance of ChaC1 in cancer prognosis across a wide variety of cancers. Additionally, the information on the SNPs of ChaC1 with altered enzymatic activities would improve the prognostic ability of these panels and facilitate treatment regimens.

Ferroptosis in antitumor therapy: Unraveling regulatory mechanisms and immunogenic potential

Ferroptosis, a recently discovered form of non-apoptotic cell death, has the potential to revolutionize anti-tumor therapy. This review highlights the regulatory mechanisms and immunogenic properties of ferroptosis, and how it can enhance the effectiveness of radio and immunotherapies in overcoming tumor resistance. However, tumor metabolism and the impact of ferroptosis on the tumor microenvironment present challenges in completely realizing its therapeutic potential. A deeper understanding of the effects of ferroptosis on tumor cells and their associated immune cells is essential for developing more effective tumor treatment strategies. This review offers a comprehensive overview of the relationship between ferroptosis and tumor immunity, and sheds new light on its application in tumor immunotherapy.

Ultrasound-based radiomics-clinical nomogram for noninvasive prediction of residual cancer burden grading in breast cancer

PURPOSE

To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients.

METHODS

This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images. Subsequently, multivariate LR (logistic regression) analysis incorporating both radiomic scores and clinical factors was performed to construct a nomogram. Finally, Receiver operating characteristics (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate and validate the diagnostic accuracy and effectiveness of the nomogram.

RESULTS

A total of 1122 patients were included in this study. Among them, 427 patients exhibited a favorable response to NAC chemotherapy, while 695 patients demonstrated a poor response to NAC therapy. The radiomics model achieved an AUC value of 0.84 in the training cohort and 0.83 in the validation cohort. The ultrasound-based radiomics-clinical nomogram achieved an AUC value of 0.90 in the training cohort and 0.91 in the validation cohort.

CONCLUSIONS

Ultrasound-based radiomics-clinical nomogram can accurately predict the effectiveness of NAC therapy by predicting RCB grading in breast cancer patients.

Pacidusin B isolated from Phyllanthus acidus triggers ferroptotic cell death in HT1080 cells

Cancer cells generally exhibit 'iron addiction' phenotypes, which contribute to their vulnerability to ferroptosis inducers. Ferroptosis is a newly discovered form of programmed cell death caused by iron-dependent lipid peroxidation. In the present study, pacidusin B, a dichapetalin-type triterpenoid from Phyllanthus acidus (L.) Skeels (Euphorbiaceae), induces ferroptosis in the HT1080 human fibrosarcoma cell line. Cells treated with pacidusin B exhibited the morphological characteristic 'ballooning' phenotype of ferroptosis. The biochemical hallmarks of ferroptosis were also observed in pacidusin B-treated cells. Both oxidative stress and ER stress play significant roles in pacidusin B-induced ferroptosis. The activation of the PERK-Nrf2-HO-1 signaling pathway led to iron overload, while inhibition of GPX4 further sensitized cancer cells to ferroptosis. Furthermore, the molecular docking study showed that pacidusin B docked in the same pocket in xCT as the ferroptosis inducer erastin. These results revealed that pacidusin B exerts anticancer effects via inducing ER-mediated ferroptotic cell death.

The Importance of HHLA2 in Solid Tumors-A Review of the Literature

Cancer immunotherapy is a rapidly developing field of medicine that aims to use the host's immune mechanisms to inhibit and eliminate cancer cells. Antibodies targeting CTLA-4, PD-1, and its ligand PD-L1 are used in various cancer therapies. However, the most thoroughly researched pathway targeting PD-1/PD-L1 has many limitations, and multiple malignancies resist its effects. Human endogenous retrovirus-H Long repeat-associating 2 (HHLA2, known as B7H5/B7H7/B7y) is the youngest known molecule from the B7 family. HHLA2/TMIGD2/KIRD3DL3 is one of the critical pathways in modulating the immune response. Recent studies have demonstrated that HHLA2 has a double effect in modulating the immune system. The connection of HHLA2 with TMIGD2 induces T cell growth and cytokine production via an AKT-dependent signaling cascade. On the other hand, the binding of HHLA2 and KIR3DL3 leads to the inhibition of T cells and mediates tumor resistance against NK cells. This review aimed to summarize novel information about HHLA2, focusing on immunological mechanisms and clinical features of the HHLA2/KIR3DL3/TMIGD2 pathway in the context of potential strategies for malignancy treatment.

Immunotherapy and drug sensitivity predictive roles of a novel prognostic model in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most significant causes of cancer-related deaths in the worldwide. Currently, predicting the survival of patients with HCC and developing treatment drugs still remain a significant challenge. In this study, we employed prognosis-related genes to develop and externally validate a predictive risk model. Furthermore, the correlation between signaling pathways, immune cell infiltration, immunotherapy response, drug sensitivity, and risk score was investigated using different algorithm platforms in HCC. Our results showed that 11 differentially expressed genes including UBE2C, PTTG1, TOP2A, SPP1, FCN3, SLC22A1, ADH4, CYP2C8, SLC10A1, F9, and FBP1 were identified as being related to prognosis, which were integrated to construct a prediction model. Our model could accurately predict patients' overall survival using both internal and external datasets. Moreover, a strong correlation was revealed between the signaling pathway, immune cell infiltration, immunotherapy response, and risk score. Importantly, a novel potential drug candidate for HCC treatment was discovered based on the risk score and also validated through ex vivo experiments. Our finds offer a novel perspective on prognosis prediction and drug exploration for cancer patients.