GCH1 induces immunosuppression through metabolic reprogramming and IDO1 upregulation in triple-negative breast cancer

Ferroptosis: a new hunter of hepatocellular carcinoma

Ferroptosis is an iron ion-dependent, regulatory cell death modality driven by intracellular lipid peroxidation that plays a key role in the development of HCC. Studies have shown that various clinical agents (e.g., sorafenib) have ferroptosis inducer-like effects and can exert therapeutic effects by modulating different key factors in the ferroptosis pathway. This implies that targeting tumor cell ferroptosis may be a very promising strategy for tumor therapy. In this paper, we summarize the prerequisites and defense systems for the occurrence of ferroptosis and the regulatory targets of drug-mediated ferroptosis action in HCC, the differences and connections between ferroptosis and other programmed cell deaths. We aim to summarize the theoretical basis, classical inducers of ferroptosis and research progress of ferroptosis in HCC cells, clued to the treatment of HCC by regulating ferroptosis network. Further investigation of the specific mechanisms of ferroptosis and the development of hepatocellular carcinoma and interventions at different stages of hepatocellular carcinoma will help us to deepen our understanding of hepatocellular carcinoma, with a view to providing new and more precise preventive as well as therapeutic measures for patients.

Lactylation-related gene signature for prognostic prediction and immune infiltration analysis in breast cancer

Background

Lactylation is implicated in various aspects of tumor biology, but its relation to breast cancer remains poorly understood. This study aimed to explore the roles of the lactylation-related genes in breast cancer and its association with the tumor microenvironment.

Methods

The expression and mutation patterns of lactylation-related genes were analyzed using the breast cancer data from The Cancer Genome Atlas (TCGA) database and GSE20685 datasets. Unsupervised clustering was used to identify two lactylation clusters. A lactylation-related gene signature was developed and validated using the training and validation cohorts. Immune cell infiltration and drug response were assessed.

Results

We analyzed the mRNA expression, copy number variations, somatic mutations, and correlation networks of 22 lactylation-related genes in breast cancer tissues. We identified two distinct lactylation clusters with different survival outcomes and immune microenvironments. We further classified the patients into two gene subtypes based on lactylation clusters and identified a 7-gene signature for breast cancer survival prognosis. The prognostic score based on this signature demonstrated prognostic value and predicted the therapeutic response.

Conclusion

Lactylation-related genes play a critical role in breast cancer by influencing tumor growth, immune microenvironment, and drug response. This lactylation-related gene signature may serve as a prognostic marker and a potential therapeutic target for breast cancer.

SRSF1 inhibits ferroptosis and reduces cisplatin chemosensitivity of triple-negative breast cancer cells through the circSEPT9/GCH1 axis

Cisplatin (DDP) is a commonly used chemotherapeutic agent for triple negative breast cancer (TNBC), but its efficacy can be limited by chemoresistance. This study aimed to explore the functional mechanism of SR-rich splicing factor 1 (SRSF1) in DDP chemosensitivity of TNBC cells. Levels of SRSF1, circular RNA septin 9 (circSEPT9), and GTP cyclohydrolase-1 (GCH1) in TNBC cells, DDP-resistant cells, and normal cells were determined. Cell viability, half-maximal inhibitory concentration (IC50) value, and proliferation were evaluated. Ferroptosis was determined by assay kits (ferric ion/ROS/MDA/GSH) and Western blot assay (SLC7A11/ACSL4). The genetic binding was analyzed by RNA immunoprecipitation and RNA pull-down assays. SRSF1, circSEPT9, and GCH1 were upregulated in TNBC cells. SRSF1 downregulation reduced IC50 to DDP of parent and drug-resistant TNBC cells and inhibited cell viability and proliferation, meanwhile, the downregulation reduced GSH/SLC7A11 levels while elevated ferric ion/ROS/MDA/ACSL4 levels, promoting ferroptosis. SRSF1 bound to and upregulated circSEPT9 and circSEPT9 blocked the ubiquitination of GCH1, thereby increasing GCH1 protein level. Overexpression of circSEPT9 and GCH1 attenuated the DDP chemosensitivity of TNBC cells by inhibiting ferroptosis. This study is the first to report the role of SRSF1 inhibitors combined with chemotherapy in TNBC, which provides a promising strategy for the treatment of TNBC. SIGNIFICANCE: Cisplatin (DDP) is a commonly used chemotherapeutic agent for triple negative breast cancer (TNBC), but its efficacy can be limited by chemoresistance. This study aimed to unravel the molecular mechanism of SR-rich splicing factor 1 (SRSF1) in DDP chemosensitivity of TNBC cells.

Exploration of the role of oxidative stress-related genes in LPS-induced acute lung injury via bioinformatics and experimental studies

During the progression of acute lung injury (ALI), oxidative stress and inflammatory responses always promote each other. The datasets analyzed in this research were acquired from the Gene Expression Omnibus (GEO) database. The Weighted Gene Co-expression Network Analysis (WGCNA) and limma package were used to obtain the ALI-related genes (ALIRGs) and differentially expressed genes (DEGs), respectively. In total, two biological markers (Gch1 and Tnfaip3) related to oxidative stress were identified by machine learning algorithms, Receiver Operator Characteristic (ROC), and differential expression analyses. The area under the curve (AUC) value of biological markers was greater than 0.9, indicating an excellent power to distinguish between ALI and control groups. Moreover, 15 differential immune cells were selected between the ALI and control samples, and they were correlated to biological markers. The transcription factor (TF)-microRNA (miRNA)-Target network was constructed to explore the potential regulatory mechanisms. Finally, based on the quantitative reverse transcription polymerase chain reaction (qRT-PCR), the expression of Gch1 and Tnfaip3 was significantly higher in ALI lung tissue than in healthy controls. In conclusion, the differences in expression profiles between ALI and normal controls were found, and two biological markers were identified, providing a research basis for further understanding the pathogenesis of ALI.

IDO1 facilitates esophageal carcinoma progression by driving the direct binding of NF-κB and CXCL10

Esophageal carcinoma (EC), one of the most lethal human malignancies, lacks effective targeted therapies. Indoleamine 2,3-dioxygenase 1 (IDO1) plays a key role in a variety of cancers, but its role and mechanism in EC are still unclear. Immunohistochemistry and qRT-PCR were used to analyze the expression of IDO1 in EC, and the prognostic value of IDO1 in EC was evaluated by Kaplan-Meier test. The in vitro and in vivo function loss/acquisition tests were performed to evaluate the biological effects of IDO1 in EC. The mechanism of action of IDO1-regulation EC was explored through Firefly luciferase & Renilla luciferase activity reporter, chromatin immunoprecipitation (ChIP) and immunofluorescence (IF) assays. Clinically, IDO1 expression was abnormally elevated in EC and positively correlated with overall survival. Functionally, IDO1 was contributed to the proliferation and migration of EC cells. Mechanically, IDO1 regulated the expression of chemokine C-X-C ligand 10 (CXCL10) by promoting the entry of NF-κB into the nucleus to combine with the promoter of CXCL10. Consistently, IDO1 facilitated EC progression may dependent on the presence of CXCL10. Moreover, NF-κB alleviated the inhibitory effect of IDO1 knockdown on EC. IDO1 drove the progression of EC by directly binding NF-κB and CXCL10, the finding that may provide an effective theoretical basis for precise therapies for EC.

GTP Cyclohydrolase Drives Breast Cancer Development and Promotes EMT in an Enzyme-Independent Manner

GTP cyclohydrolase (GCH1) is the rate-limiting enzyme for tetrahydrobiopterin (BH4) biosynthesis. The catalysis of BH4 biosynthesis is tightly regulated for physiological neurotransmission, inflammation, and vascular tone. Paradoxically, BH4 has emerged as an oncometabolite regulating tumor growth, but the effects on tumor development remain controversial. Here, we found that GCH1 potentiated the growth of triple-negative breast cancer (TNBC) and HER2+ breast cancer and transformed nontumor breast epithelial cells. Independent of BH4 production, GCH1 protein induced epithelial-to-mesenchymal transition by binding to vimentin (Vim), which was mediated by HSP90. Conversely, GCH1 ablation impaired tumor growth, suppressed Vim in TNBC, and inhibited EGFR/ERK signaling while activating the p53 pathway in estrogen receptor-positive tumor cells. GCH1 deficiency increases tumor cell sensitivity to HSP90 inhibition and endocrine treatments. In addition, high GCH1 correlated with poor breast cancer survival. Together, this study reveals an enzyme-independent oncogenic role of GCH1, presenting it as a potential target for therapeutic development.

SIGNIFICANCE

GTP cyclohydrolase functions as an oncogene in breast cancer and binds vimentin to induce epithelial-to-mesenchymal transition independently of its enzyme activity, which confers targetable vulnerabilities for developing breast cancer treatment strategies.

Involvement of the kynurenine pathway in breast cancer: updates on clinical research and trials

Breast cancer (BrCa) is the leading cause of cancer incidence and mortality in women worldwide. While BrCa treatment has been shown to be highly successful if detected at an early stage, there are few effective strategies to treat metastatic tumours. Hence, metastasis remains the main cause in most of BrCa deaths, highlighting the need for new approaches in this group of patients. Immunotherapy has been gaining attention as a new treatment for BrCa metastasis and the kynurenine pathway (KP) has been suggested as one of the potential targets. The KP is the major biochemical pathway in tryptophan (TRP) metabolism, catabolising TRP to nicotinamide adenine dinucleotide (NAD+). The KP has been reported to be elevated under inflammatory conditions such as cancers and that its activity suppresses immune surveillance. Dysregulation of the KP has previously been reported implicated in BrCa. This review aims to discuss and provide an update on the current mechanisms involved in KP-mediated immune suppression and cancer growth. Furthermore, we also provide a summary on 58 studies about the involvement of the KP and BrCa and five clinical trials targeting KP enzymes and their outcome.

Breast cancer prognosis and immunological characteristics are predicted using the m6A/m5C/m1A/m7G-related long noncoding RNA signature

According to statistics, breast cancer (BC) has replaced lung cancer as the most common cancer in the world. Therefore, specific detection markers and therapeutic targets need to be explored as a way to improve the survival rate of BC patients. We first identified m6A/m5C/m1A/m7G-related long noncoding RNAs (MRlncRNAs) and developed a model of 16 MRlncRNAs. Kaplan-Meier survival analysis was applied to assess the prognostic power of the model, while univariate Cox analysis and multivariate Cox analysis were used to assess the prognostic value of the constructed model. Then, we constructed a nomogram to illustrate whether the predicted results were in good agreement with the actual outcomes. We tried to use the model to distinguish the difference in sensitivity to immunotherapy between the two groups and performed some analyses such as immune infiltration analysis, ssGSEA and IC50 prediction. To explore the novel anti-tumor drug response, we reclassified the patients into two clusters. Next, we assessed their response to clinical treatment by the R package pRRophetic, which is determined by the IC50 of each BC patient. We finally identified 11 MRlncRNAs and based on them, a risk model was constructed. In this model, we found good agreement between calibration plots and prognosis prediction. The AUC of ROC curves was 0.751, 0.734, and 0.769 for 1-year, 2-year, and 3-year overall survival (OS), respectively. The results showed that the IC50 was significantly different between the risk groups, suggesting that the risk groups can be used as a guide for systemic treatment. We regrouped patients into two clusters based on 11 MRlncRNAs expression. Next, we conducted immune scores for 2 clusters, which showed that cluster 1 had higher stromal scores, immune scores and higher estimated (microenvironment) scores, demonstrating that TME of cluster 1 was different from cluster 2. The results of this study support that MRlncRNAs can predict tumor prognosis and help differentiate patients with different sensitivities to immunotherapy as a basis for individualized treatment for BC patients.

Effect of metabolism on the immune microenvironment of breast cancer

Breast cancer (BC) is a highly prevalent primary malignancy worldwide with poor prognosis. Despite the development of aggressive interventions, mortality due to BC remains high. BC cells reprogram nutrient metabolism to adapt to the energy acquisition and progression of the tumor. The metabolic changes in cancer cells are closely related to the abnormal function and effect of immune cells and immune factors, including chemokines, cytokines, and other related effector molecules in the tumor microenvironment (TME), leading to tumor immune escape, whereby the complex crosstalk between immune cells and cancer cells has been considered the key mechanism regulating cancer progression. In this review, we summarized the latest findings on metabolism-related processes in the immune microenvironment during BC progression. Our findings showing the impact of metabolism on the immune microenvironment may suggest new strategies for regulating the immune microenvironment and attenuating BC through metabolic interventions.

Construction and validation of a macrophage polarization-related prognostic index to predict the overall survival in patients with early-stage triple-negative breast cancer

Background

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease and the current prognostic system cannot meet the clinical need. Interactions between immune responsiveness and tumor cells plays a key role in the progression of TNBC and macrophages are vital component of immune cells. A prognostic model based on macrophages may have great accuracy and clinical utility.

Methods

For model development, we screened early stage (without metastasis) TNBC patients from The Cancer Genome Atlas (TCGA) database. We extracted messenger RNA (mRNA) expression data and clinical data including age, race, tumor size, lymph node status and tumor stage. The follow up time and vital status were also retrieved for overall survival calculation. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) was used to calculate the immune cell composition of each sample. Weighted gene co-expression network analysis (WGCNA) was used to identify M1-like macrophage-related genes. Combining least absolute shrinkage and selection operator (LASSO) with multivariate Cox regression, the M1-like macrophage polarization-related prognostic index (MRPI) was established. We obtained TNBC patients in Gene Expression Omnibus (GEO) database through PAM50 method and retrieved the mRNA expression data and survival data. The Harrell's concordance index (CI), the area under the receiver operating characteristic (ROC) curves (AUCs) and the calibration curve were used to evaluate the developed model.

Results

We obtained 166 early TNBC cases and 113 normal tissue cases for model building, along with 76 samples from GSE58812 cohort for model validation. CIBERSORT analysis suggested obvious infiltration of macrophages, especially M1-like macrophages in early TNBC. Four genes were eventually identified for the construction of MPRI in the training set. The AUCs at 2 years, 3 years, and 5 years in the training cohort were 0.855, 0.881 and 0.893, respectively; and the AUCs at 2 years, 3 years, and 5 years in the validation cohort were 0.887, 0.792 and 0.722, respectively. Calibration curves indicated good predictive ability and high consistency of our model.

Conclusions

MRPI is a promising biomarker for predicting the prognosis of early-stage TNBC, which may indicate personalized treatment and follow-up strategies and thus may improve the prognosis.

UPLC-Q-TOF/MS Based Plasma Metabolomics for Identification of Paeonol's Metabolic Target in Endometriosis

Endometriosis is a common gynecological illness in women of reproductive age that significantly decreases life quality and fertility. Paeonol has been shown to play an important part in endometriosis treatments. Understanding the mechanism is critical for treating endometriosis. In this study, autologous transplantation combined with a 28 day ice water bath was used to create a rat model of endometriosis with cold clotting and blood stagnation. The levels of estradiol and progesterone in plasma were detected by ELISA, and the pathological changes of ectopic endometrial tissue were examined by H&E staining, which proved the efficacy of paeonol. For metabolomic analysis of plasma samples, UPLC-Q/TOF-MS was combined with multivariate statistical analysis to identify the influence of paeonol on small molecule metabolites relevant to endometriosis. Finally, the key targets were screened using a combination of network pharmacology and molecular docking approaches. The results showed that the pathological indexes of rats were improved and returned to normal levels after treatment with paeonol, which was the basis for confirming the efficacy of paeonol. Metabolomics results identified 13 potential biomarkers, and paeonol callbacks 7 of them, involving six metabolic pathways. Finally, four key genes were found for paeonol therapy of endometriosis, and the results of molecular docking revealed a significant interaction between paeonol and the four key genes. This study was successful in establishing a rat model of endometriosis with cold coagulation and blood stagnation. GCH1, RPL8, PKLR, and MAOA were the key targets of paeonol in the treatment of endometriosis. It is also demonstrated that metabolomic techniques give the potential and environment for comprehensively understanding drug onset processes.

In Silico Investigation of the Human GTP Cyclohydrolase 1 Enzyme Reveals the Potential of Drug Repurposing Approaches towards the Discovery of Effective BH4 Therapeutics

The GTP cyclohydrolase 1 enzyme (GTPCH1) is the rate-limiting enzyme of the tetrahydrobiopterin (BH₄) biosynthetic pathway. Physiologically, BH₄ plays a crucial role as an essential cofactor for the production of catecholamine neurotransmitters, including epinephrine, norepinephrine and dopamine, as well as the gaseous signaling molecule, nitric oxide. Pathological levels of the cofactor have been reported in a number of disease states, such as inflammatory conditions, neuropathic pain and cancer. Targeting the GTPCH1 enzyme has great potential in the management of a number of disease pathologies associated with dysregulated BH₄ physiology. This study is an in silico investigation of the human GTPCH1 enzyme using virtual screening and molecular dynamic simulation to identify molecules that can be repurposed to therapeutically target the enzyme. A three-tier molecular docking protocol was employed in the virtual screening of a comprehensive library of over 7000 approved medications and nutraceuticals in order to identify hit compounds capable of binding to the GTPCH1 binding pocket with the highest affinity. Hit compounds were further verified by molecular dynamic simulation studies to provide a detailed insight regarding the stability and nature of the binding interaction. In this study, we identify a number of drugs and natural compounds with recognized anti-inflammatory, analgesic and cytotoxic effects, including the aminosalicylate olsalazine, the antiepileptic phenytoin catechol, and the phlorotannins phlorofucofuroeckol and eckol. Our results suggest that the therapeutic and clinical effects of hit compounds may be partially attributed to the inhibition of the GTPCH1 enzyme. Notably, this study offers an understanding of the off-target effects of a number of compounds and advocates the potential role of aminosalicylates in the regulation of BH₄ production in inflammatory disease states. It highlights an in silico drug repurposing approach to identify a potential means of safely targeting the BH₄ biosynthetic pathway using established therapeutic agents.

Splicing factor SF3B3, a NS5-binding protein, restricts ZIKV infection by targeting GCH1

Zika virus (ZIKV), a positive-sense single-stranded RNA virus, causes congenital ZIKV syndrome in children and Guillain-Barré Syndrome (GBS) in adults. ZIKV expresses nonstructural protein 5 (NS5), a large protein that is essential for viral replication. ZIKV NS5 confers the ability to evade interferon (IFN) signalling; however, the exact mechanism remains unclear. In this study, we employed affinity pull-down and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses and found that splicing factor 3b subunit 3 (SF3B3) is associated with the NS5-Flag pull-down complex through interaction with NS5. Functional assays showed that SF3B3 overexpression inhibited ZIKV replication by promoting IFN-stimulated gene (ISG) expression whereas silencing of SF3B3 inhibited expression of ISGs to promote ZIKV replication. GTP cyclohydrolase I (GCH1) is the first and rate-limiting enzyme in tetrahydrobiopterin (BH4) biosynthesis. NS5 upregulates the expression of GCH1 during ZIKV infection. And GCH1 marginally promoted ZIKV replication via the IFN pathway. Additionally, GCH1 expression is related to the regulation of SF3B3. Overexpression of the SF3B3 protein effectively reduced GCH1 protein levels, whereas SF3B3 knockdown increased its levels. These findings indicated that ZIKV NS5 binding protein SF3B3 contributed to the host immune response against ZIKV replication by modulating the expression of GCH1.

Targeting T-cell metabolism to boost immune checkpoint inhibitor therapy

Immune checkpoint inhibitors (ICIs) have shown promising therapeutic effects in the treatment of advanced solid cancers, but their overall response rate is still very low for certain tumor subtypes, limiting their clinical scope. Moreover, the high incidence of drug resistance (including primary and acquired) and adverse effects pose significant challenges to the utilization of these therapies in the clinic. ICIs enhance T cell activation and reverse T cell exhaustion, which is a complex and multifactorial process suggesting that the regulatory mechanisms of ICI therapy are highly heterogeneous. Recently, metabolic reprogramming has emerged as a novel means of reversing T-cell exhaustion in the tumor microenvironment; there is increasing evidence that T cell metabolic disruption limits the therapeutic effect of ICIs. This review focuses on the crosstalk between T-cell metabolic reprogramming and ICI therapeutic efficacy, and summarizes recent strategies to improve drug tolerance and enhance anti-tumor effects by targeting T-cell metabolism alongside ICI therapy. The identification of potential targets for altering T-cell metabolism can significantly contribute to the development of methods to predict therapeutic responsiveness in patients receiving ICI therapy, which are currently unknown but would be of great clinical significance.

Targeting ferroptosis, the achilles' heel of breast cancer: A review

Ferroptosis is referred as a novel type of cell death discovered in recent years with the feature of the accumulation of iron-dependent lipid reactive oxygen species. Breast cancer is one of the most common malignant cancers in women. There is increasing evidence that ferroptosis can inhibit breast cancer cell growth, improve the sensitivity of chemotherapy and radiotherapy and inhibit distant metastases. Therefore, ferroptosis can be regarded a new target for tumor suppression and may expand the landscape of clinical treatment of breast cancer. This review highlights the ferroptosis mechanism and its potential role in breast cancer treatment to explore new therapeutic strategies of breast cancer.

GPX4-independent ferroptosis—a new strategy in disease’s therapy

Ferroptosis is a form of programmed cell death characterized by intracellular iron accumulation and lipid peroxidation, and earlier studies identified glutathione peroxidase 4 (GPX4) as an essential regulator of this process. Ferroptosis plays an essential role in tumors, degenerative diseases, and ischemia-reperfusion injury. However, researchers have found that inhibition of GPX4 does not entirely suppress ferroptosis in certain diseases, or cells express resistance to ferroptosis agonists that inhibit GPX4. As research progresses, it has been discovered that there are multiple regulatory pathways for ferroptosis that are independent of GPX4. The study of GPX4-independent ferroptosis pathways can better target ferroptosis to prevent and treat various diseases. Here, the currently inhibited pulmonary GPX4-dependent ferroptosis pathways will be reviewed.

Ferritinophagy, a form of autophagic ferroptosis: New insights into cancer treatment

Ferritinophagy, a form of autophagy, is also an important part of ferroptosis, a type of regulated cell death resulting from abnormal iron metabolism involving the production of reactive oxygen species. As ferroptosis, autophagy and cancer have been revealed, ferritinophagy has attracted increasing attention in cancer development. In this review, we discuss the latest research progress on ferroptosis, autophagy-associated ferroptosis led by ferritinophagy, the regulators of ferritinophagy and promising cancer treatments that target ferritinophagy. Ferritinophagy is at the intersection of ferroptosis and autophagy and plays a significant role in cancer development. The discussed studies provide new insights into the mechanisms of ferritinophagy and promising related treatments for cancer.

A comprehensive genomic and transcriptomic dataset of triple-negative breast cancers

Molecular subtyping of triple-negative breast cancer (TNBC) is essential for understanding the mechanisms and discovering actionable targets of this highly heterogeneous type of breast cancer. We previously performed a large single-center and multiomics study consisting of genomics, transcriptomics, and clinical information from 465 patients with primary TNBC. To facilitate reusing this unique dataset, we provided a detailed description of the dataset with special attention to data quality in this study. The multiomics data were generally of high quality, but a few sequencing data had quality issues and should be noted in subsequent data reuse. Furthermore, we reconduct data analyses with updated pipelines and the updated version of the human reference genome from hg19 to hg38. The updated profiles were in good concordance with those previously published in terms of gene quantification, variant calling, and copy number alteration. Additionally, we developed a user-friendly web-based database for convenient access and interactive exploration of the dataset. Our work will facilitate reusing the dataset, maximize the values of data and further accelerate cancer research.

Measurement(s)	RNA expression profiling • whole-exome sequencing (WES) • somatic mutations • copy number alterations (CNAs)
Technology Type(s)	RNA sequencing • DNA sequencing • OncoScan CNV assay
Factor Type(s)	Intervention or procedure
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Location	China

3D Collagen Fiber Concentration Regulates Treg Cell Infiltration in Triple Negative Breast Cancer

Background

Triple negative breast cancer (TNBC) is characterized by poor prognosis and a lack of effective therapeutic agents owing to the absence of biomarkers. A high abundance of tumor-infiltrating regulatory T cells (Tregs) was associated with worse prognosis in malignant disease. Exploring the association between Treg cell infiltration and TNBC will provide new insights for understanding TNBC immunosuppression and may pave the way for developing novel immune-based treatments.

Materials and Methods

Patients from TCGA were divided into Treg-high (Treg-H) and Treg-low (Treg-L) groups based on the abundance of Tregs according to CIBERSORT analysis. The association between expression level of Tregs and the clinical characteristics as well as prognosis of breast cancer were evaluated. Next, a Treg-related prognostic model was established after survival-dependent univariate Cox and LASSO regression analysis, companied with an external GEO cohort validation. Then, GO, KEGG and GSEA analyses were performed between the Treg-H and Treg-L groups. Masson and Sirius red/Fast Green staining were applied for ECM characterization. Accordingly, Jurkat T cells were encapsulated in 3D collagen to mimic the ECM microenvironment, and the expression levels of CD4, FOXP3 and CD25 were quantified according to immunofluorescence staining.

Results

The expression level of Tregs is significantly associated with the clinical characteristics of breast cancer patients, and a high level of Treg cell expression indicates a poor prognosis in TNBC. To further evaluate this, a Treg-related prognostic model was established that accurately predicted outcomes in both TCGA training and GEO validation cohorts of TNBC patients. Subsequently, ECM-associated signaling pathways were identified between the Treg-H and Treg-L groups, indicating the role of ECM in Treg infiltration. Since we found increasing collagen concentrations in TNBC patients with distant migration, we encapsulated Jurkat T cells within a 3D matrix with different collagen concentrations and observed that increasing collagen concentrations promoted the expression of Treg biomarkers, supporting the regulatory role of ECM in Treg infiltration.

Conclusion

Our results support the association between Treg expression and breast cancer progression as well as prognosis in the TNBC subtype. Moreover, increasing collagen density may promote Treg infiltration, and thus induce an immunosuppressed TME.

Expression of ferroptosis-related gene correlates with immune microenvironment and predicts prognosis in gastric cancer

The study is to explore the role of ferroptosis-related genes (FRGs) in the occurrence and development of gastric cancer (GC), and to construct a new prognosis signature to predict the prognosis in GC. Clinical information and corresponding RNA data of GC patients were downloaded from TCGA and GEO databases. Consensus clustering was performed to identify new molecular subgroups. ESTIMATE, CIBERSORT, McpCounter and TIMER algorithm were used to analyze the infiltration of immune cells in two molecular subgroups. LASSO algorithm and multivariate Cox analysis were used to construct a prognostic risk signature. Functional analysis was conducted to elucidate the underlying mechanisms. Finally, the FRPGs were verified by Quantitative Real-Time PCR. We obtained 16 FRGs and divided GC patients into two subgroups by consistent clustering. Cluster C1 with a higher abundance of immune cell infiltration but lower probability in response to immunotherapy, it was reasonable to speculate that Cluster C1 was in accordance with the immune rejection type. Functional analysis showed that the biological process of DEGs in training cohort mainly included immune globulin, and human immune response mediated by circulating immune globulin. GSEA analysis showed that compared with Cluster C2, Cluster C1 showed lower expression in lipid metabolism. The nomogram combined with risk signature and clinical features can accurately predict the prognosis of GC patients. We identified two molecular subtypes, Clusters C1 and C2. In Cluster C1, patients with poor prognosis present with a hyperimmune status and low lipid metabolism, and we speculate that Cluster C1 was in accordance with the immune rejection type. The risk model based on FRPGs can accurately predict the prognosis of GC. These results indicated that ferroptosis is associated with TIME, and deserved considerable attention in determining immunotherapy treatment strategy for GC patients.

Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network

Background: Considering the role of immunity and ferroptosis in the invasion, proliferation and treatment of cancer, it is of interest to construct a model of prognostic-related differential expressed immune-related ferroptosis genes (PR-DE-IRFeGs), and explore the ferroptosis-related biological processes in esophageal cancer (ESCA).

Methods: Four ESCA datasets were used to identify three PR-DE-IRFeGs for constructing the prognostic model. Validation of our model was based on analyses of internal and external data sets, and comparisons with past models. With the biological-based enrichment analysis as a guide, exploration for ESCA-related biological processes was undertaken with respect to the immune microenvironment, mutations, competing endogenous RNAs (ceRNA), and copy number variation (CNV). The model’s clinical applicability was measured by nomogram and correlation analysis between risk score and gene expression, and also immune-based and chemotherapeutic sensitivity.

Results: Three PR-DE-IRFeGs (DDIT3, SLC2A3, and GCH1), risk factors for prognosis of ESCA patients, were the basis for constructing the prognostic model. Validation of our model shows a meaningful capability for prognosis prediction. Furthermore, many biological functions and pathways related to immunity and ferroptosis were enriched in the high-risk group, and the role of the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network in ESCA is supported. Also, the KMT2D mutation is associated with our risk score and SLC2A3 expression. Overall, the prognostic model was associated with treatment sensitivity and levels of gene expression.

Conclusion: A novel, prognostic model was shown to have high predictive value. Biological processes related to immune functions, KMT2D mutation, CNV and the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 network were involved in ESCA progression.