A Novel Ferroptosis-Related Biomarker Signature to Predict Overall Survival of Esophageal Squamous Cell Carcinoma

CircMMP11 is a Potential Recurrence Biomarker and Facilitates Progression of Esophageal Squamous Cell Carcinoma

Esophageal cancer is a deadly tumor with a high mortality rate and unsatisfactory treatment effect. Circular RNAs (circRNAs), as a new kind of noncoding RNA molecules, were found to play a key role in variety of tumors. This study aimed to explore the participation of hsa_circ_0062558 (circMMP11) in the recurrence of ESCC and its role in ESCC progression. The expression of circMMP11 in tissue specimens and cells was measured using the RT-qPCR method. RNase R treatment assay and Actinomycin D treatment assay verified the stability of circMMP11. Receiver Operating Characteristic (ROC) curve was conducted to evaluate the clinical significance of circMMP11 in predicting postoperative recurrence. The capacities of circMMP11 on cellular behaviors were measured using cell counting kit (CCK-8) and Transwell assays. The circMMP11 expression was raised in ESCC tissues. The circMMP11 in tumor tissues of the recurrence/metastasis group was higher than that in the non-recurrence/metastasis group. ROC curve showed that circMMP11 in tumor tissues could detect the postoperative recurrence/metastasis of the patients with an area under the ROC curve (AUC) of 0.838. Silencing circMMP11 led to a reduction in the proliferative, migratory, and invasive capacities of ESCC cells, and miR-671-5p inhibitor partially diminished the inhibitory effects of si-circMMP11. The high circMMP11 expression in postoperative tissues of patients with ESCC is correlated with recurrence and metastasis, and it has potential predictive value for postoperative recurrence and metastasis of patients. Inhibition of circMMP11 repressed ESCC cell behaviors by regulating miR-671-5p, which may be a potential target for early diagnosis of recurrence and treatment of ESCC.

Targeting ferroptosis in gastrointestinal tumors: Interplay of iron-dependent cell death and autophagy

Ferroptosis is a regulated cell death mechanism distinct from apoptosis, autophagy, and necroptosis, marked by iron accumulation and lipid peroxidation. Since its identification in 2012, it has developed into a potential therapeutic target, especially concerning GI disorders like PC, HCC, GC, and CRC. This interest arises from the distinctive role of ferroptosis in the progression of diseases, presenting a new avenue for treatment where existing therapies fall short. Recent studies emphasize the promise of focusing on ferroptosis to fight GI cancers, showcasing its unique pathophysiological mechanisms compared to other types of cell death. By comprehending how ferroptosis aids in the onset and advancement of GI diseases, scientists aim to discover novel drug targets and treatment approaches. Investigating ferroptosis in gastrointestinal disorders reveals exciting possibilities for novel therapies, potentially revolutionizing cancer treatment and providing renewed hope for individuals affected by these tumors.

Development and validation of a prognostic model based on disulfidptosis-related ferroptosis genes: DRD4 and SLC2A3 as biomarkers for predicting prognosis in colon cancer

Background

Disulfidptosis and ferroptosis are emerging cell death modalities crucial to cancer progression, yet their prognostic potential in colon cancer (CC) remains underexplored. This study develops and validates a prognostic model based on DRD4 and SLC2A3, two genes involved in key biological processes in CC. DRD4 regulates cell proliferation, migration, and apoptosis, while SLC2A3 enhances glucose uptake via the Warburg effect, promoting tumor growth. High expression of both genes is linked to poor prognosis, advanced stages, and increased aggressiveness, enabling precise stratification of patients and accurate prognostic predictions.

Methods

Transcriptomic and clinical data from 476 CC samples and 41 normal colon samples were obtained from The Cancer Genome Atlas (TCGA) database, with 452 patient samples utilized for survival analysis. A training cohort and a validation cohort were generated through random allocation. Disulfidptosis-related ferroptosis genes (DRFGs) were identified using Pearson correlation analysis, and a prognostic model was built using the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. External validation was performed using the Gene Expression Omnibus (GEO) datasets (GSE17538 and GSE38832), and clinical samples were further analyzed through immunohistochemistry. Predictors in the nomogram included age, gender, tumor stage, and risk score. The C-index of the final model was used to assess its prognostic accuracy.

Results

The results were validated using external cohorts from the GEO database and immunohistochemistry experiments. A prognostic model incorporating DRD4 and SLC2A3 effectively stratified CC patients into high- and low-risk groups, revealing distinct differences in survival times, immune landscapes, and biological characteristics. High expression levels of DRD4 and SLC2A3 correlated with advanced clinicopathological stages and poor prognosis, with a C-index of 0.75 indicating strong predictive accuracy. Immunohistochemistry confirmed the upregulation of both genes in CC tissues, further validating the model's clinical relevance.

Conclusions

This DRFG-based prognostic model offers an effective tool for predicting clinical outcomes in CC and can guide personalized treatment strategies. The upregulation of DRD4 and SLC2A3 suggests their potential as therapeutic targets. Future studies should focus on elucidating the underlying mechanisms of these biomarkers to enhance their clinical application.

Deciphering the heterogeneity and plasticity of the tumor microenvironment in liver cancer provides insights for prognosis

Liver cancer exhibits diverse molecular characteristics and distinct immune cell infiltration patterns, which significantly influence patient outcomes. In this study, we thoroughly examined the liver cancer tumor environment by analyzing data from 419,866 individual cells across nine datasets involving 99 patients. By categorizing patients into different groups based on their immune cell profiles, including immune deficiency, B cells-enriched, T cells-enriched and macrophages-enriched, we better understood how these cells change in various patient subgroups. Our investigation of liver metastases from intestinal cancer uncovered a group of mast cells that might promote metastasis through pathways like inositol phosphate metabolism. Using genomic and clinical data from The Cancer Genome Atlas, we identified specific cell components linked to tumor characteristics and genetics. Our detailed study of cancer-associated fibroblasts (CAFs) revealed how they adapt and acquire new functions in the tissue environment, highlighting their flexibility. Additionally, we found a significant connection between CAF-related genes and the prognosis of hepatocellular carcinoma patients. This research provides valuable insights into the makeup of the liver cancer tumor environment and its profound impact on patient outcomes, offering fresh perspectives for managing this challenging disease.

Exploration and validation of a novel reactive oxygen species-related signature for predicting the prognosis and chemotherapy response of patients with bladder cancer

Background

Reactive Oxygen Species (ROS), a hallmark of cancer, is related to prognosis, tumor progression, and treatment response. Nevertheless, the correlation of ROS-based molecular signature with clinical outcome and immune cell infiltration has not been thoroughly studied in bladder cancer (BLCA). Accordingly, we aimed to thoroughly examine the role and prognostic value of ROS-related genes in BLCA.

Methods

We obtained RNA sequencing and clinical data from The Cancer Genome Atlas (TCGA) for bladder cancer (BLCA) patients and identified ROS-associated genes using the GeneCards and Molecular Signatures Database (MSigDB). We then analyzed differential gene expression between BLCA and normal tissues and explored the functions of these ROS-related genes through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analysis. Prognostic ROS-related genes were identified using Univariate Cox regression (UCR) and LASSO analyses, which were further refined in a Multivariate Cox Regression (MCR) analysis to develop a Prognostic Signature (PS). This PS was validated in the GSE13507 cohort, assessing its predictive power with Kaplan-Meier survival and time-dependent ROC curves. To forecast BLCA outcomes, we constructed a nomogram integrating the PS with clinical variables. We also investigated the signature's molecular characteristics through Gene Set Enrichment Analysis (GSEA), Immune Cell Infiltration (ICI), and Tumor Mutational Burden (TMB) analyses. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict chemotherapy responses based on the PS. Additionally, we screened for Small-Molecule Drugs (SMDs) targeting ROS-related genes using the CMAP database. Finally, we validated our findings by checking protein levels of the signature genes in the Human Protein Atlas (HPA) and confirmed the role of Aldo-keto reductase family 1 member B1 (AKR1B1) through in vitro experiments.

Results

The constructed and validated PS that comprised 17 ROS-related genes exhibited good performance in predicting overall survival (OS), constituting an independent prognostic biomarker in BLCA patients. Additionally, we successfully established a nomogram with superior predictive capacity, as indicated by the calibration plots. The bioinformatics analysis findings showcased the implication of PS in several oncogenic pathways besides tumor ICI regulation. The PS was negatively associated with the TMB. The high-risk group patients had greater chemotherapy sensitivity in comparison to low-risk group patients. Further, 11 candidate SMDs were identified for treating BLCA. The majority of gene expression exhibited a correlation with the protein expression. In addition, the expression of most genes was consistent with protein expression. Furthermore, to test the gene reliability we constructed, AKR1B1, one of the seventeen genes identified, was used for in-depth validation. In vitro experiments indicate that siRNA-mediated AKR1B1 silencing impeded BLCA cell viability, migration, and proliferation.

Conclusions

We identified a PS based on 17 ROS-related genes that represented independent OS prognostic factors and 11 candidate SMDs for BLCA treatment, which may contribute to the development of effective individualized therapies for BLCA.

A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity

Intratumor heterogeneity significantly challenges the accuracy of existing prognostic models for esophageal squamous cell carcinoma (ESCC) by introducing biases related to the varied genetic and molecular landscapes within tumors. Traditional models, relying on single-sample, single-region bulk RNA sequencing, fall short of capturing the complexity of intratumor heterogeneity. To fill this gap, we developed a computational model for intratumor heterogeneity corrected signature (ITHCS) by employing both multiregion bulk and single-cell RNA sequencing to pinpoint genes that exhibit consistent expression patterns across different tumor regions but vary significantly among patients. Utilizing these genes, we applied multiple machine-learning algorithms for sophisticated feature selection and model construction. The ITHCS model significantly outperforms existing prognostic indicators in accuracy and generalizability, markedly reducing sampling biases caused by intratumor heterogeneity. This improvement is especially notable in the prognostic assessment of early-stage ESCC patients, where the model exhibits exceptional predictive power. Additionally, we found that the risk score based on ITHCS may be associated with epithelial-mesenchymal transition characteristics, indicating that high-risk patients may exhibit a diminished efficacy to immunotherapy.

Ferroptosis in thyroid cancer: Potential mechanisms, effective therapeutic targets and predictive biomarker

Thyroid cancer is a prevalent endocrine malignancy whose global incidence has risen over the past several decades. Ferroptosis, a regulated form of cell death distinguished by the excessive buildup of iron-dependent lipid peroxidates, stands out from other programmed cell death pathways in terms of morphological and molecular characteristics. Increasing evidence suggests a close association between thyroid cancer and ferroptosis, that is, inducing ferroptosis effectively suppresses the proliferation of thyroid cancer cells and impede tumor advancement. Therefore, ferroptosis represents a promising therapeutic target for the clinical management of thyroid cancer in clinical settings. Alterations in ferroptosis-related genes hold potential for prognostic prediction in thyroid cancer. This review summarizes current studies on the role of ferroptosis in thyroid cancer, elucidating its mechanisms, therapeutic targets, and predictive biomarkers. The findings underscore the significance of ferroptosis in thyroid cancer and offer valuable insights into the development of innovative treatment strategies and accurate predictors for the thyroid cancer.

A novel fatty acid metabolism-related signature identifies MUC4 as a novel therapy target for esophageal squamous cell carcinoma

Fatty acid metabolism has been identified as an emerging hallmark of cancer, which was closely associated with cancer prognosis. Whether fatty acid metabolism-related genes (FMGs) signature play a more crucial role in biological behavior of esophageal squamous cell carcinoma (ESCC) prognosis remains unknown. Thus, we aimed to identify a reliable FMGs signature for assisting treatment decisions and prognosis evaluation of ESCC. In the present study, we conducted consensus clustering analysis on 259 publicly available ESCC samples. The clinical information was downloaded from The Cancer Genome Atlas (TCGA, 80 ESCC samples) and Gene Expression Omnibus (GEO) database (GSE53625, 179 ESCC samples). A consensus clustering arithmetic was used to determine the FMGs molecular subtypes, and survival outcomes and immune features were evaluated among the different subtypes. Kaplan-Meier analysis and the receiver operating characteristic (ROC) was applied to evaluate the reliability of the risk model in training cohort, validation cohort and all cohorts. A nomogram to predict patients' 1-year, 3-year and 5-year survival rate was also studied. Finally, CCK-8 assay, wound healing assay, and transwell assay were implemented to evaluate the inherent mechanisms of FMGs for tumorigenesis in ESCC. Two subtypes were identified by consensus clustering, of which cluster 2 is preferentially associated with poor prognosis, lower immune cell infiltration. A fatty acid (FA) metabolism-related risk model containing eight genes (FZD10, TACSTD2, MUC4, PDLIM1, PRSS12, BAALC, DNAJA2 and ALOX12B) was established. High-risk group patients displayed worse survival, higher stromal, immune and ESTIMATE scores than in the low-risk group. Moreover, a nomogram revealed good predictive ability of clinical outcomes in ESCC patients. The results of qRT-PCR analysis revealed that the MUC4 and BAALC had high expression level, and FZD10, PDLIM1, TACSTD2, ALOX12B had low expression level in ESCC cells. In vitro, silencing MUC4 remarkably inhibited ESCC cell proliferation, invasion and migration. Our study fills the gap of FMGs signature in predicting the prognosis of ESCC patients. These findings revealed that cluster subtypes and risk model of FMGs had effects on survival prediction, and were expected to be the potential promising targets for ESCC.

Identification and Validation of Immune Implication of R-Spondin 1 and an R-Spondin 1-Related Prognostic Signature in Esophagus Cancer

R-spondin 1 (RSPO1), which encodes a secretory-activating protein, is a promising therapeutic target for various tumors. The aim of this study was to establish a robust RSPO1-related signature specific to esophageal cancer (ESCA). Our comprehensive study involved meticulous analysis of RSPO1 expression in ESCA tissues and validation across ESCA cell lines and clinical samples using The Cancer Genome Atlas (TCGA) and GTEx databases. Using TCGA-ESCA dataset, we employed single-sample gene set enrichment analysis (ssGSEA) to elucidate the complex interaction between RSPO1 expression and the abundance of 22 specific immune cell types infiltrating ESCA. The biological significance of RSPO1 was further elucidated using KEGG, GO, and GSEA, demonstrating its relevance to pivotal tumor and immune pathways. This study culminated in the construction of prognostic nomograms enriched by calibration curves, facilitating the projection of individual survival probabilities at intervals of one, three, and five years. A substantial decrease in RSPO1 expression was observed within ESCA tissues and cell lines compared to their normal esophageal counterparts, and a significant decrease in the proportion of activated dendritic cells was evident within ESCA, accompanied by an augmented presence of macrophages and naive B cells relative to normal tissue. GSEA and KEGG analyses showed that RSPO1 was associated with tumor and immune pathways. Additionally, an independent prognostic risk score based on the RSPO1-related gene signature was developed and validated for patients with ESCA. Finally, RT-qPCR and western blotting were performed to confirm RSPO1 expression in normal and ESCA cell lines and tissue samples. In summary, our investigation underscores the pivotal role of RSPO1 in orchestrating tumor immunity and proposes RSPO1 as a prospective target for immunotherapeutic interventions in ESCA. Furthermore, the intricate profile of the two RSPO1-related genes has emerged as a promising predictive biomarker with notable potential for application in ESCA.

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

Solanine induces ferroptosis in colorectal cancer cells through ALOX12B/ADCY4 molecular axis

OBJECTIVES

Colorectal cancer (CRC) is the fourth most commonly diagnosed cancer worldwide. Solanine is a phytochemical extracted from traditional Chinese medicine with widely reported anticancer effects. Here, we investigated the potential role of solanine in regulating ferroptosis in CRC cells and scrutinized the molecular mechanism.

METHODS

Cell growth and cytotoxicity were examined using CCK-8 proliferation assay and lactate dehydrogenase assay. Oxidative stress was determined by measuring glutathione (GSH), malondialdehyde, and reactive oxygen species (ROS) levels. Subcellular changes in mitochondria were examined by transmission electron microscopy. Gene and protein expression levels were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Protein-protein interaction was determined by co-immunoprecipitation.

KEY FINDINGS

Solanine arrested cell proliferation in CRC cells and induced typical ferroptotic changes. Solanine treatment promoted ROS production, lipid peroxidation, and cell membrane disruption, while the cellular level of antioxidant GSH was reduced upon solanine treatment. ALOX12B was identified as a molecular mediator of solanine to promote ferroptosis. Solanine treatment upregulated ALOX12B levels and silencing ALOX12B could suppress solanine-induced ferroptosis. Further, ADCY4 was found to physically associate with ALOX12B and maintain ALOX12B protein stability. Silencing ADCY4 destabilized ALOX12B and attenuated solanine-induced ferroptosis.

CONCLUSIONS

Our data demonstrated the ferroptosis-inducing effect of solanine in CRC cells, and revealed ALOX12B/ADCY4 molecular axis as the ferroptosis mediator of solanine. Solanine may synergize with existing ferroptosis inducer as an anticancer strategy in CRC, which warrants further validation in animal experiments.

Multi-omics analysis reveals cuproptosis and mitochondria-based signature for assessing prognosis and immune landscape in osteosarcoma

Background

Osteosarcoma (OSA), the most common primary mesenchymal bone tumor, is a health threat to children and adolescents with a dismal prognosis. While cuproptosis and mitochondria dysfunction have been demonstrated to exert a crucial role in tumor progression and development, the mechanisms by which they are regulated in OSA still await clarification.

Methods

Two independent OSA cohorts containing transcriptome data and clinical information were collected from public databases. The heterogeneity of OSA were evaluated by single cell RNA (scRNA) analysis. To identify a newly molecular subtype, unsupervised consensus clustering was conducted. Cox relevant regression methods were utilized to establish a prognostic gene signature. Wet lab experiments were performed to confirm the effect of model gene in OSA cells.

Results

We determined 30 distinct cell clusters and assessed OSA heterogeneity and stemness scRNA analysis. Then, univariate Cox analysis identified 24 candidate genes which were greatly associated with the prognosis of OSA. Based on these prognostic genes, we obtained two molecular subgroups. After conducting step Cox regression, three model genes were selected to construct a signature showing a favorable performance to forecast clinical outcome. Our proposed signature could also evaluate the response to chemotherapy and immunotherapy of OSA cases.

Conclusion

We generated a novel risk model based on cuproptosis and mitochondria-related genes in OSA with powerful predictive ability in prognosis and immune landscape.

Cross-talk of pyroptosis-based subtypes, the development of a risk classifier and immune responses in cervical cancer

BACKGROUND

Cervical cancer (CC) is one of the most common gynecology malignancies and has a dismal survival outcome. The prognostic value of pyroptosis and its role in the regulation of immune metabolism in CC remain unclear.

METHODS

Two independent CC cohorts collected from public databases were integrated for unsupervised cluster analysis. All CC cases were assigned to different subsets based on the pyroptosis-related genes (PRGs). The differentially expressed genes (DEGs) between different subclusters were included in stepwise Cox regression for the risk classifier establishment. Next, single-cell sequencing analysis was conducted to explore the cellular location of each model gene. The CIBERSORT algorithm was applied to estimate immunocytes infiltration. Finally, a series of functional experiments were performed to detect the role of CDH3 in CC.

RESULTS

Based on the 52 PRGs, the combined CC cohort was clustered into two subsets (C1 (n = 259) and C2 (n = 242)). Survival and Cox regression methods were used to create a pyroptosis-based risk classifier including four PRGs (PEG3, FSCN1, CDH3 and SLC2A1). For the immune environment in CC, the high-risk group had a lower infiltration level of B cells, memory-activated CD4 T cells and CD8 T cells and a higher infiltration abundance of neutrophils. The expression pattern of model genes was confirmed in CC cell lines by PCR assay. Furthermore, we observed that knockdown of CDH3 could suppress CC cell proliferation.

CONCLUSION

Our project could offer promising reference for prognosis assessment, immune metabolism prediction and clinical decision-making of patients with CC.

Role of ferroptosis in esophageal cancer and corresponding immunotherapy

Esophageal cancer (EC) is one of the most common digestive system malignancies in the world. The combined modality treatment of EC is usually surgery and radiation therapy, however, its clinical efficacy for advanced patients is relatively limited. Ferroptosis, a new type of iron-dependent programmed cell death, is different from apoptosis, necrosis and autophagy. In recent years, many studies have further enlightened that ferroptosis plays an essential role in the occurrence, development and metastasis of tumors. Targeting ferroptosis stimulates a new direction for further exploration of oncologic treatment regimens. Furthermore, ferroptosis has a critical role in the immune microenvironment of tumors. This paper reviews the mechanism of ferroptosis and the ferroptosis research progress in the treatment of EC. We further elaborate the interaction between ferroptosis and immunotherapy, and the related mechanisms of ferroptosis participation in the immunotherapy of EC, so as to provide new directions and ideas for the treatment of EC.

JUND facilitates proliferation and angiogenesis of esophageal squamous cell carcinoma cell via MAPRE2 up-regulation

OBJECTIVE

Esophageal squamous cell carcinoma (ESCC) is a globally aggressive malignant tumor. This study aimed to investigate the mechanism of JUND in ESCC development via MAPRE2.

METHODS

ESCC cells (KYSE-450 and ECA109) were transfected with small interfering RNA (si)-JUND, si-MAPRE2, si-JUND, or pcDNA3.1-MAPRE2. JUND and MAPRE2 expression in ESCC cells was detected with quantitative real-time polymerase chain reaction and western blot. Cell counting kit-8 and 5-ethynyl-2'-deoxyuridine assays were used to determine ESCC cell proliferation. Dual-luciferase reporter gene and chromatin immunoprecipitation assays were performed to assess binding between JUND and MAPRE2. Human umbilical vein endothelial cells (HUVECs) were co-cultured with ESCC cell supernatants. Angiogenesis was assessed with an in vitro angiogenesis assay. Western blot was conducted to evaluate the expression of angiogenic proteins [vascular endothelial growth factor A (VEGFA), matrix metallopeptidase 9 (MMP-9), and angiopoietin-2 (ang2)].

RESULTS

The levels of expression of JUND and MAPRE2 were high in ESCC cells. Mechanistically, JUND bound to MAPRE2 promoter and increased MAPRE2 transcription. Downregulation of JUND or MAPRE2 inhibited KYSE-450 and ECA109 cell proliferation and reduced the levels of expression of VEGFA, MMP-9, and ang2 and tube formation in HUVECs co-cultured with ESCC cell supernatants. MAPRE2 upregulation counteracted the inhibitory effects of JUND silencing on cell proliferative and angiogenic capabilities in ESCC.

CONCLUSIONS

JUND promoted MAPRE2 transcription, thereby facilitating cell proliferative and angiogenic abilities in ESCC.

Integrated single-cell and transcriptome sequencing analyses develops a metastasis-based risk score system for prognosis and immunotherapy response in uveal melanoma

Background: Uveal melanoma (UM) is the most frequent ocular neoplasm with a strong metastatic ability. The prognostic value of metastasis-associated genes (MAGs) of UM remains unclear. It is urgent to develop a prognostic score system according to the MAGs of UM. Methods: Unsupervised clustering was used to identify MAGs-based molecular subtypes. Cox methods were utilized to generate a prognostic score system. The prognostic ability of the score system was detected by plotting ROC and survival curves. The immune activity and underlying function were depicted by CIBERSORT GSEA algorithms. Results: Gene cluster analysis determined two MAGs-based subclusters in UM, which were remarkably different in clinical outcomes. A risk score system containing six MAGs (COL11A1, AREG, TIMP3, ADAM12, PRRX1 and GAS1) was set up. We employed ssGSEA to compare immune activity and immunocyte infiltration between the two risk groups. Notch, JAK/STAT and mTOR pathways were greatly enriched in the high-risk group. Furthermore, we observed that knockdown of AREG could inhibit UM proliferation and metastasis by in vitro assays. Conclusion: The MAGs-based subtype and score system in UM can enhance prognosis assessment, and the core system provides valuable reference for clinical decision-making.

Characteristics and response to next-generation sequencing-guided therapy in locally advanced or metastatic esophageal cancer

Esophageal cancer (EC) is a main cause of cancer-related deaths. However, genomic alterations and the clinical value of next-generation sequencing (NGS) in advanced or metastatic EC for precision therapy remain largely unclear. Herein, we performed comprehensive analyses on a cohort of 47 individuals with advanced or metastatic EC who underwent NGS between May 2017 and February 2020. Eventually, 227 mutated genes were identified in the cohort. TP53, NQO1, DPYD, GSTM1, XRCC1 and ERCC1 were the most mutated genes and associated with immune cell infiltration, autophagy and hypoxia. Patients who received NGS-guided treatments exhibited better objective remission rate (ORR) (72.22%), disease control rate (DCR) (88.89%), overall survival (OS) (P = .0019) and progression-free survival (PFS) (P = .0077) than those not receiving NGS-guided therapies. The multivariate analyses further demonstrated that the NGS-guided therapy was an independently prognostic factor (OS: hazard radio [HR] 0.31, 95% coincidence interval [CI] 0.1-0.97, P = .04). In conclusion, we depicted a comprehensive mutational landscape of 47 patients with locally advanced or metastatic EC and illustrated the utility of NGS testing to guide clinical management in improving ORR, DCR, OS and PFS.

Construction of a ferroptosis scoring system and identification of LINC01572 as a novel ferroptosis suppressor in lung adenocarcinoma

Background: Ferroptosis is a novel process of programmed cell death driven by excessive lipid peroxidation that is associated with the development of lung adenocarcinoma. N6-methyladenosine (m6a) modification of multiple genes is involved in regulating the ferroptosis process, while the predictive value of N6-methyladenosine- and ferroptosis-associated lncRNA (FMRlncRNA) in the prognosis of patients remains with LUAD remains unknown. Methods: Unsupervised cluster algorithm was applied to generate subcluster in LUAD according to ferroptosis-associated lncRNA. Stepwise Cox analysis and LASSO algorithm were applied to develop a prognostic model. Cellular location was detected by single-cell analysis. Also, we conducted Gene set enrichment analysis (GSEA) enrichment, immune microenvironment and drug sensitivity analysis. In addition, the expression and function of the LINC01572 were investigated by several in vitro experiments including qRT-PCR, cell viability assays and ferroptosis assays. Results: A novel ferroptosis-associated lncRNAs-based molecular subtype containing two subclusters were determined in LUAD. Then, we successfully created a risk model according to five ferroptosis-associated lncRNAs (LINC00472, MBNL1-AS1, LINC01572, ZFPM2-AS1, and TMPO-AS1). Our nominated model had good stability and predictive function. The expression patterns of five ferroptosis-associated lncRNAs were confirmed by polymerase chain reaction (PCR) in LUAD cell lines. Knockdown of LINC01572 significantly inhibited cell viability and induced ferroptosis in LUAD cell lines. Conclusion: Our data provided a risk score system based on ferroptosis-associated lncRNAs with prognostic value in LUAD. Moreover, LINC01572 may serve as a novel ferroptosis suppressor in LUAD.

Exploration of prognostic genes and risk signature in breast cancer patients based on RNA binding proteins associated with ferroptosis

Background: Breast cancer (BRCA) is a life-threatening malignancy in women with an unsatisfactory prognosis. The purpose of this study was to explore the prognostic biomarkers and a risk signature based on ferroptosis-related RNA-binding proteins (FR-RBPs). Methods: FR-RBPs were identified using Spearman correlation analysis. Differentially expressed genes (DEGs) were identified by the "limma" R package. The univariate Cox and multivariate Cox analyses were executed to determine the prognostic genes. The risk signature was constructed and verified with the training set, testing set, and validation set. Mutation analysis, immune checkpoint expression analysis in high- and low-risk groups, and correlation between risk signature and chemotherapeutic agents were conducted using the "maftools" package, "ggplot2" package, and the CellMiner database respectively. The Human Protein Atlas (HPA) database was employed to confirm protein expression trends of prognostic genes in BRCA and normal tissues. The expression of prognostic genes in cell lines was verified by Real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-meier (KM) plotter database analysis was applied to predict the correlation between the expression levels of signature genes and survival statuses. Results: Five prognostic genes (GSPT2, RNASE1, TIPARP, TSEN54, and SAMD4A) to construct an FR-RBPs-related risk signature were identified and the risk signature was validated by the International Cancer Genome Consortium (ICGC) cohort. Univariate and multivariate Cox regression analysis demonstrated the risk score was a robust independent prognostic factor in overall survival prediction. The Tumor Mutational Burden (TMB) analysis implied that the high- and low-risk groups responded differently to immunotherapy. Drug sensitivity analysis suggested that the risk signature may serve as a chemosensitivity predictor. The results of GSEA suggested that five prognostic genes might be related to DNA replication and the immune-related pathways. RT-qPCR results demonstrated that the expression trends of prognostic genes in cell lines were consistent with the results from public databases. KM plotter database analysis suggested that high expression levels of GSPT2, RNASE1, and SAMD4A contributed to poor prognoses. Conclusion: In conclusion, this study identified the FR-RBPs-related prognostic genes and developed an FR-RBPs-related risk signature for the prognosis of BRCA, which will be of great significance in developing new therapeutic targets and prognostic molecular biomarkers for BRCA.

A pan-cancer analysis of the oncogenic role of zinc finger protein 419 in human cancer

Background

As a ferroptosis-related gene, the polymorphism of zinc finger protein 419 (ZNF419) at the splice donor site may generate renal cell carcinoma-associated novel minor histocompatibility antigen ZAPHIR. However, the role of ZNF419 in prognosis and immunology in human tumors remains largely unknown. This study aimed to visualize the prognostic landscape of ZNF419 at pan-cancer level and explore the relationship between ZNF419 expression and the tumor immune microenvironment.

Method

Pan-cancer and mutation data were downloaded from TCGA databases and analyzed through R (version 3.6.4) and its suitable packages. Differential ZNF419 expression and prognosis were analyzed. Correlations with ferroptosis-related genes, pathway analysis, tumor stemness, heterogeneity, mutation landscape, and RNA modifications were also explored. The relationships between ZNF419 expression and tumor immunity were investigated through the TIMER and ESTIMATE methods.

Result

ZNF419 was differentially expressed between tumor and normal samples and was associated with overall survival, disease-specific survival and progression-free interval for STES, KIRC, LIHC, LUSC, PRAD, and BLCA. We found the interaction between ZNF419 and FANCD2 might involve in ferroptosis in pan-cancer level. In addition, the mutation frequencies of STES, KIRC, LIHC, LUSC, PRAD, and BLCA were 1.5%, 0.3%, 0.3%, 1.9%, 0.2%, and 0.7%, respectively. We detected that the expression of ZNF419 was closely correlated with most immune checkpoint genes and immune regulatory genes. Furthermore, we found that the ZNF419 expression level was negatively related to the immune score in the six cancers mentioned above. The expression of ZNF419 was significantly associated with various infiltrating immune cells, such as CD4+ T cells, CD8+ T cells, and macrophages in patients with KIRC, PRAD, and LUSC but was only significantly related to macrophages in BLCA patients.

Conclusion

ZNF419 might serve as a potential prognostic and immunological pan-cancer biomarker, especially for KIRC, LIHC, LUSC, PRAD, and BLCA.

A more novel and robust gene signature predicts outcome in patients with esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The tumor microenvironment (TME) mainly comprises tumor cells and tumor-infiltrating immune cells mixed with stromal components. The latest research has displayed that tumor immune cell infiltration (ICI) is closely connected with the ESCC patients' clinical prognosis. This study was designed to construct a gene signature based on the ICI of ESCC to predict prognosis.

METHODS

Based on the selection criteria we set, the eligible ESCC cases from the GSE53625 and TCGA-ESCA datasets were chosen for the training cohort and the validation cohort, respectively. Unsupervised clustering detailed grouped ESCC cases of the training cohort based on the ICI profile. We determined the differential expression genes (DEGs) between the ICI clusters, and, subsequently, we adopted the univariate Cox analysis to recognize DEGs with prognostic potential. These screened DEGs underwent a Lasso regression, which then generated a gene signature. The harvested signature's predictive ability was further examined by the Kaplan-Meier analysis, Cox analysis, ROC, IAUC, and IBS. More importantly, we listed similar studies in the most recent year and compared theirs with ours. We performed the functional annotation, immune relevant signature correlation analysis, and immune infiltrating analysis to thoroughly understand the functional mechanism of the signature and the immune cells' roles in the gene signature's predicting capacity.

RESULTS

A sixteen-gene signature (ARSD, BCAT1, BIK, CLDN11, DLEU7-AS1, GGH, IGFBP2, LINC01037, LINC01446, LINC01497, M1AP, PCSK2, PCSK5, PPP2R2A, TIGD7, and TMSB4X) was generated from the Lasso model. We then confirmed the signature as having solid and stable prognostic capacity by several statistical methods. We revealed the superiority of our signature after comparing it to our predecessors, and the GSEA uncovered the specifically mechanism of action related to the gene signature. Two immune relevant signatures, including GZMA and LAG3 were identified associating with our signature. The immune-infiltrating analysis identified crucial roles of resting mast cells, which potentially support the sixteen-gene signature's prognosis ability.

CONCLUSIONS

We discovered a robust sixteen-gene signature that can accurately predict ESCC prognosis. The immune relevant signatures, GZMA and LAG3, and resting mast cells infiltrating were closely linked to the sixteen-gene signature's ability.

Ferroptosis and its emerging role in esophageal cancer

The occurrence and development of tumors involve a series of life activities of cells, among which cell death has always been a crucial part in the research of tumor mechanisms and treatment methods. Ferroptosis is a non-apoptotic form of cell death, which is characterized by lipid peroxidation accumulation and further cell membrane rupture caused by excessive production of intracellular oxygen free radicals dependent on iron ions. Esophageal cancer is one of the common digestive tract tumors. Patients in the early stage are mainly treated with surgery, and the curative effect is awe-inspiring. However, surgery is far from enough for terminal patients, and it is the best choice to combine radiotherapy and chemotherapy before the operation or during the perioperative period. Although the treatment plan for patients with advanced esophageal cancer is constantly being optimized, we are disappointed at the still meager 5-year survival rate of patients and the poor quality of life. A series of complex problems, such as increased chemotherapy drug resistance and decreased radiotherapy sensitivity of esophageal cancer cells, are waiting for us to tackle. Perhaps ferroptosis can provide practical and feasible solutions and bring new hope to patients with advanced esophageal cancer. The occurrence of ferroptosis is related to the dysregulation of iron metabolism, lipid metabolism, and glutamate metabolism. Therefore, these dysregulated metabolic participant proteins and signaling pathways are essential entry points for using cellular ferroptosis to resist the occurrence and development of cancer cells. This review first introduced the main regulatory mechanisms of ferroptosis. It then summarized the current research status of ferroptosis in esophageal cancer, expecting to provide ideas for the research related to ferroptosis in esophageal cancer.

Screening of ferroptosis-related genes with prognostic effect in colorectal cancer by bioinformatic analysis

Colorectal cancer (CRC) remains a common malignant tumor of digestive tract with high incidence rate and high mortality in the worldwide. The current clinical treatments of CRC often fail to achieve satisfactory results. Searching for more effective prediction or prognosis biomarkers, or developing more targeted therapeutic schedule may help to improve the outcomes of CRC patients. Here, we tried to study the effect of ferroptosis-related genes on CRC prognosis and make it clearer that ferroptosis has connection with immune environment. First, we obtained gene expression data of CRC and normal tissues, as well as corresponding clinical data from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were intersected with ferroptosis-related gene set downloaded from FerrDb database, and 93 abnormally expressed ferroptosis-related genes were obtained. Then, these genes were analyzed for functional enrichment. Univariate Cox regression and multivariate Cox regression analyses were performed to establish prognostic model based on ferroptosis-related genes. In the process of exploring the correlation between prognostic genes and immune infiltration, we found that these genes were closely related to B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages and other cells in CRC. In addition, we found a large proportion of plasma cells and macrophages in TCGA-COADREAD. Finally, a prognostic nomogram of ferroptosis-related genes was established, including age, sex, grade and other predicted values. To summary, we established a prognostic model of colorectal cancer (CRC) based on ferroptosis-related genes and further explored the relationship between these genes with immune microenvironment.

Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron-dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis-related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune-associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA-ESCC database were designated as the training cohort. A ten-FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real-time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten-FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high-risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.

A Novel Ferroptosis-Related Gene Signature to Predict Prognosis of Esophageal Carcinoma

Objective

This study aimed to develop a novel ferroptosis-related gene-based prognostic signature for esophageal carcinoma (ESCA).

Methods

The TCGA-ESCA gene expression profiles and corresponding clinical data were downloaded from the TCGA database. Ferroptosis-related genes were identified from the literature and public databases, which were intersected with the differentially expressed genes between ESCA and normal samples. After univariate Cox regression and random forest analyses, several ferroptosis-related feature genes were identified and used to construct a prognostic signature. Then, the prognostic value of the complex value and the correlation of the complex value with immune cell infiltration were analyzed. Moreover, function analysis, mutation analysis, and molecular docking on the ferroptosis-related feature genes were performed.

Results

Based on the TCGA dataset and ferroptosis pathway genes, 1929 ferroptosis-related genes were preliminarily selected. Following univariate Cox regression analysis and survival analysis, 14 genes were obtained. Then, random forest analysis identified 10 ferroptosis key genes. These 10 genes were used to construct a prognostic complex value. It was found that low complex value indicated better prognosis compared with high complex value. In different ESCA datasets, there were similar differences in the proportion of immune cell distribution between the high and low complex value groups. Furthermore, TNKS1BP1, AC019100.7, KRI1, BCAP31, and RP11-408E5.5 were significantly correlated with ESCA tumor location, lymph node metastasis, and age of patients. KRI1 had the highest mutation frequency. BCAP31 had the strongest binding ability with small molecules DB12830, DB05812, and DB07307.

Conclusion

We constructed a novel ferroptosis-related gene signature, which has the potential to predict patient survival and tumor-infiltrating immune cells of ESCA.

The Immunological Contribution of a Novel Metabolism-Related Signature to the Prognosis and Anti-Tumor Immunity in Cervical Cancer

Cervical cancer is the most frequently diagnosed malignancy in the female reproductive system. Conventional stratification of patients based on clinicopathological characters has gradually been outpaced by a molecular profiling strategy. Our study aimed to identify a reliable metabolism-related predictive signature for the prognosis and anti-tumor immunity in cervical cancer. In this study, we extracted five metabolism-related hub genes, including ALOX12B, CA9, FAR2, F5 and TDO2, for the establishment of the risk score model. The Kaplan-Meier curve suggested that patients with a high-risk score apparently had a worse prognosis in the cervical cancer training cohort (TCGA, n = 304, p < 0.0001), validation cohort (GSE44001, n = 300, p = 0.0059) and pan-cancer cohorts (including nine TCGA tumors). Using a gene set enrichment analysis (GSEA), we observed that the model was correlated with various immune-regulation-related pathways. Furthermore, pan-cancer cohorts and immunohistochemical analysis showed that the infiltration of tumor infiltrating lymphocytes (TILs) was lower in the high-score group. Additionally, the model could also predict the prognosis of patients with cervical cancer based on the expression of immune checkpoints (ICPs) in both the discovery and validation cohorts. Our study established and validated a metabolism-related prognostic model, which might improve the accuracy of predicting the clinical outcome of patients with cervical cancer and provide guidance for personalized treatment.

Endoplasmic Reticulum Stress-Related Four-Biomarker Risk Classifier for Survival Evaluation in Esophageal Cancer

Purpose

Esophageal cancer (EC) is a lethal digestive tumor worldwide with a dismal clinical outcome. Endoplasmic reticulum (ER) stress poses essential implications for a variety of tumor malignant behaviors. Here, we set up an ER stress-based risk classifier for assessing patient outcome and exploiting robust targets for medical decision-making of EC cases.

Methods

340 EC cases with transcriptome and survival data from two independent public datasets (TCGA and GEO) were recruited for this project. Cox regression analyses were employed to create a risk classifier based on ER stress-related genes (ERGs) which were strongly linked to EC cases' outcomes. Then, we detected and confirmed the predictive ability of our proposed classifier via a host of statistical methods, including survival analysis and ROC method. In addition, immune-associated algorithm was implemented to analyze the immune activity of EC samples.

Results

Four EGRs (BCAP31, HSPD1, PDHA1, and UBE2D1) were selected to build an EGR-related classifier (ERC). This classifier could distinguish the patients into different risky subgroups. The remarkable differences in patient outcome between the two groups were observed, and similar results were also confirmed in GEO cohort. In terms of the immune analysis, the ERC could forecast the infiltration level of immunocytes, such as Tregs and NK cells.

Conclusion

We created a four-ERG risk classifier which displays the powerful capability of survival evaluation for EC cases.

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.

A TRP Family Based Signature for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma

Purpose

Head and neck squamous cell carcinoma (HNSCC) is a classical type of head and neck cancers, with heterogeneous clinical outcome. This project is set out to create a robust risk signature based on TRP family genes (TFGs) for prognosis evaluation in HNSCC.

Methods

Based on the HNSCC sample data from the TCGA website, we integrated expression profile of TFGs for 490 HNSCC cases. We explore the interactions among TFGs using STRING tool. The TFGs-based signature (TFBS) was created by Cox relative analyses. In addition, we conducted GSEA to identify the underlying signaling pathways of the specific TFGs in HNSCC. The immune landscape of HNSCC patients was analyzed by CIBERSORT and ssGSEA algorithms.

Results

A total of 6 TFGs (TRPC1, TRPC3, TRPC6, TRPV2, TRPV4, and TRPM8) closely associated with prognosis of HNSCC cases were screened to create TFBS. TFBS predicted that the TFBS-high group presented dismal patient outcome. Cox regression revealed the favorable independent value of TFBS. ROC analysis showed the robust power of TFBS for prognosis forecasting. GSEA determined several crucial pathways related with HNSCC, which are the p53 pathway, TNF-alpha signaling via NFKB, and hypoxia. Moreover, immune-related analysis showed that patients in the TFBS-high group were more likely in immunosuppressive status.

Conclusion

Our proposed TFBS could serve as a favorable indicator to forecast the survival outcome of HNSCC cases and offer prominent therapy guidance.

Identification of a Hypoxia-Related lncRNA Biomarker Signature for Head and Neck Squamous Cell Carcinoma

Purpose. Hypoxia is a leading hallmark of tumors, which is associated with carcinogenicity and dismal patient outcome. In this project, we tended to detect the prognostic value of hypoxic lncRNA and further generate a hypoxic lncRNA-based model in head and neck squamous cell carcinoma (HNSCC). Methods. We integrated the transcriptome and clinical information of HNSCC based on TCGA dataset. Univariate-multivariate Cox analysis was implemented to develop the signature according to hypoxia-related lncRNAs (HRlncRNAs) with greatly prognostic power in HNSCC. Next, the biomarker signature was tested using survival analysis and ROC plots. Moreover, we used GSEA to uncover the potential pathways of HRlncRNAs, and CIBERSORT and ssGSEA tools were applied to mirror the immune status of HNSCC patients. Results. Nine HRlncRNAs (LINC00460, AC144831.1, AC116914.2, MIAT, MSC-AS1, LINC01980, MYOSLID, AL357033.4, and LINC02195) were determined to develop a HRlncRNA-related signature (HRLS). High-HRLS group was associated with dismal patient outcome using survival analysis. Moreover, the HRLS was superior to classical clinical traits in forecasting survival rate of samples with HNSCC. GSEA unearthed the top six hallmarks in the HRLS-high group individuals. In addition, the HRLS was also bound up with the infiltration of macrophages, CD8 T cells, and activated mast cells. Conclusion. Our nominated nine-HRlncRNA risk model is robust and valuable tool for forecasting patient outcome in HNSCC.

Ferroptosis patterns and tumor microenvironment infiltration characterization in esophageal squamous cell cancer

Background: Esophageal Squamous Cell Cancer (ESCC) is an aggressive disease associated with a poor prognosis. As a newly defined form of regulated cell death, ferroptosis plays a crucial role in cancer development and treatment and might be a promising therapeutic target. However, the expression patterns of ferroptosis-related genes (FRGs) in ESCC remain to be systematically analyzed. Methods: First, we retrieved the transcriptional profile of ESCC from TCGA and GEO datasets (GSE47404, GSE23400, and GSE53625) and performed unsupervised clustering to identify different ferroptosis patterns. Then, we used the ssGSEA algorithm to estimate the immune cell infiltration of these patterns and explored the differences in immune cell abundance. Common genes among patterns were finally identified as signature genes of ferroptosis patterns. Results: Herein, we depicted the multi-omics landscape of FRGs through integrated bioinformatics analysis and identified three ESCC subtypes with distinct immune characteristics: clusters A-C. Cluster C was abundant in CD8⁺ T cells and other immune cell infiltration, while cluster A was immune-barren. By comparing the differently expressed genes between clusters of diverse datasets, we defined a gene signature for each cluster and successfully validated it in the TCGA-ESCC dataset. Conclusion: We provided a comprehensive insight into the expression pattern of ferroptosis genes and their interaction with immune cell infiltration. Additionally, we established a gene signature to define the ferroptosis patterns, which might be used to predict the response to immunotherapy.