Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma

Faecal Microbiota Transplantation Alleviates Ferroptosis after Ischaemic Stroke

Ischaemic stroke can induce changes in the abundance of gut microbiota constituents, and the outcome of stroke may also be influenced by the gut microbiota. This study aimed to determine whether gut microbiota transplantation could rescue changes in the gut microbiota and reduce ferroptosis after stroke in rats. Male Sprague-Dawley rats (6 weeks of age) were subjected to ischaemic stroke by middle cerebral artery occlusion (MCAO). Fecal samples were collected for 16S ribosomal RNA (rRNA) sequencing to analyze the effects of FMT on the gut microbiota. Neurological deficits were evaluated using the Longa score. triphenyl tetrazolium chloride (TTC) staining was performed in the brain, and kits were used to measure malondialdehyde (MDA), iron, and glutathione (GSH) levels in the ipsilateral brain of rats. Western blotting was used to detect the protein expression levels of glutathione peroxidase 4 (GPX4), solute carrier family 7 member 11 (SLC7A11), and the transferrin receptor 2 (TFR2) in the ipsilateral brain of rats. Stroke induced significant changes in the gut microbiota, and FMT ameliorated these changes. TTC staining results showed that FMT reduced cerebral infarct volume. In addition, FMT diminished MDA and iron levels and elevated GSH levels in the ipsilateral brain. Western blot analysis showed that FMT increased GPX4 and SLC7A11 protein expression and decreased TFR2 protein expression in the ipsilateral brain after stroke. FMT can reverse gut microbiota dysbiosis, reduce cerebellar infarct volume, and decrease ferroptosis after stroke.

Harnessing ferroptosis for enhanced sarcoma treatment: mechanisms, progress and prospects

Sarcoma is a malignant tumor that originates from mesenchymal tissue. The common treatment for sarcoma is surgery supplemented with radiotherapy and chemotherapy. However, patients have a 5-year survival rate of only approximately 60%, and sarcoma cells are highly resistant to chemotherapy. Ferroptosis is an iron-dependent nonapoptotic type of regulated programmed cell death that is closely related to the pathophysiological processes underlying tumorigenesis, neurological diseases and other conditions. Moreover, ferroptosis is mediated via multiple regulatory pathways that may be targets for disease therapy. Recent studies have shown that the induction of ferroptosis is an effective way to kill sarcoma cells and reduce their resistance to chemotherapeutic drugs. Moreover, ferroptosis-related genes are related to the immune system, and their expression can be used to predict sarcoma prognosis. In this review, we describe the molecular mechanism underlying ferroptosis in detail, systematically summarize recent research progress with respect to ferroptosis application as a sarcoma treatment in various contexts, and point out gaps in the theoretical research on ferroptosis, challenges to its clinical application, potential resolutions of these challenges to promote ferroptosis as an efficient, reliable and novel method of clinical sarcoma treatment.

SIMarker: Cellular similarity detection and its application to diagnosis and prognosis of liver cancer

BACKGROUND

The emergence of single-cell technology offers a unique opportunity to explore cellular similarity and heterogeneity between precancerous diseases and solid tumors. However, there is lacking a systematic study for identifying and characterizing similarities at single-cell resolution.

METHODS

We developed SIMarker, a computational framework to detect cellular similarities between precancerous diseases and solid tumors based on gene expression at single-cell resolution. Taking hepatocellular carcinoma (HCC) as a case study, we quantified the cellular and molecular connections between HCC and cirrhosis. Core analysis modules of SIMarker is publicly available at https://github.com/xmuhuanglab/SIMarker ("SIM" means "similarity" and "Marker" means "biomarkers).

RESULTS

We found PGA5+ hepatocytes in HCC showed cirrhosis-like characteristics, including similar transcriptional programs and gene regulatory networks. Consequently, the genes constituting the gene expression program of these cirrhosis-like subpopulations were designated as cirrhosis-like signatures (CLS). Strikingly, our utilization of CLS enabled the development of diagnosis and prognosis biomarkers based on within-sample relative expression orderings of gene pairs. These biomarkers achieved high precision and concordance compared with previous studies.

CONCLUSIONS

Our work provides a systematic method to investigate the clinical translational significance of cellular similarities between HCC and cirrhosis, which opens avenues for identifying similar paradigms in other categories of cancers and diseases.

Analysis of the factors influencing moderate to poor performance status in patients with cancer after chemotherapy: a cross-sectional study comparing three models

There are no models for assessing the factors that determine moderate to poor performance status in patients with cancer after chemotherapy. This study investigated the influencing factors and identified the best model for predicting moderate-poor performance status. A convenience sampling method was used. Demographic and clinical data and evaluation results for fatigue, pain, quality of life and Eastern Cooperative Oncology Group status were collected three days after the end of chemotherapy. Decision tree, random forest and logistic regression models were constructed. Ninety-four subjects in the case group had moderate to poor performance status, and 365 subjects in the control group had no or mild activity disorders. The random forest model was the most accurate model. Physical function, total protein, general quality of life within one week before chemotherapy, hemoglobin, pain symptoms and globulin were the main factors. Total protein and hemoglobin levels reflect nutritional status, and globulin levels are an index of liver function. Therefore, physical function, nutritional status, general quality of life and pain symptoms within one week before chemotherapy and liver function can be used to predict moderate-poor performance status. Nurses should pay more attention to patients with poor physical function, poor nutritional status, lower quality of life and pain symptoms after chemotherapy.

Impact of curcumin on ferroptosis-related genes in colorectal cancer: Insights from in-silico and in-vitro studies

Colorectal cancer (CRC) is responsible for a significant number of cancer-related fatalities worldwide. Researchers are investigating the therapeutic potential of ferroptosis, a type of iron-dependent controlled cell death, in the context of CRC. Curcumin, a natural compound found in turmeric, exhibits anticancer properties. This study explores the effects of curcumin on genes related to ferroptosis (FRGs) in CRC. To gather CRC data, we used the Gene Expression Profiling Interactive Analysis (GEPIA) and Gene Expression Omnibus (GEO) databases, while FRGs were obtained from the FerrDb database and PubMed. We identified 739 CRC differentially expressed genes (DEGs) in CRC and discovered 39 genes that were common genes between FRGs and CRC DEGs. The DEGs related to ferroptosis were enriched with various biological processes and molecular functions, including the regulation of signal transduction and glucose metabolism. Using the Drug Gene Interaction Database (DGIdb), we predicted drugs targeting CRC-DEGs and identified 17 potential drug targets. Additionally, we identified eight essential proteins related to ferroptosis in CRC, including MYC, IL1B, and SLC1A5. Survival analysis revealed that alterations in gene expression of CDC25A, DDR2, FABP4, IL1B, SNCA, and TFAM were associated with prognosis in CRC patients. In SW480 human CRC cells, treatment with curcumin decreased the expression of MYC, IL1B, and EZH2 mRNA, while simultaneously increasing the expression of SLCA5 and CAV1. The findings of this study suggest that curcumin could regulate FRGs in CRC and have the potential to be utilized as a therapeutic agent for treating CRC.

The recent advancements of ferroptosis in the diagnosis, treatment and prognosis of ovarian cancer

Ovarian cancer affects the female reproductive system and is the primary cause of cancer related mortality globally. The imprecise and non-specific nature of ovarian cancer symptoms often results in patients being diagnosed at an advanced stage, with metastatic lesions extending beyond the ovary. This presents a significant clinical challenge and imposes a substantial economic burden on both patients and society. Despite advancements in surgery, chemotherapy, and immunotherapy, the prognosis for most patients with ovarian cancer remains unsatisfactory. Therefore, the development of novel treatment strategies is imperative. Ferroptosis, a distinct form of regulated cell death, characterized by iron-dependent lipid peroxidation, differs from autophagy, apoptosis, and necrosis, and may hold promise as a novel cell death. Numerous studies have demonstrated the involvement of ferroptosis in various conventional signaling pathways and biological processes. Recent investigations have revealed the significant contribution of ferroptosis in the initiation, progression, and metastasis of diverse malignant tumors, including ovarian cancer. Moreover, ferroptosis exhibits a synergistic effect with chemotherapy, radiotherapy, and immunotherapy in restraining the proliferation of ovarian cancer cells. The aforementioned implies that ferroptosis holds considerable importance in the management of ovarian cancer and has the potential to serve as a novel therapeutic target. The present review provides a comprehensive overview of the salient features of ferroptosis, encompassing its underlying mechanisms and functional role in ovarian cancer, along with the associated signaling pathways and genes. Furthermore, the review highlights the prospective utility of ferroptosis in the treatment of ovarian cancer.

Acyl-CoA synthase ACSL4: an essential target in ferroptosis and fatty acid metabolism

ABSTRACT

Long-chain acyl-coenzyme A (CoA) synthase 4 (ACSL4) is an enzyme that esterifies CoA into specific polyunsaturated fatty acids, such as arachidonic acid and adrenic acid. Based on accumulated evidence, the ACSL4-catalyzed biosynthesis of arachidonoyl-CoA contributes to the execution of ferroptosis by triggering phospholipid peroxidation. Ferroptosis is a type of programmed cell death caused by iron-dependent peroxidation of lipids; ACSL4 and glutathione peroxidase 4 positively and negatively regulate ferroptosis, respectively. In addition, ACSL4 is an essential regulator of fatty acid (FA) metabolism. ACSL4 remodels the phospholipid composition of cell membranes, regulates steroidogenesis, and balances eicosanoid biosynthesis. In addition, ACSL4-mediated metabolic reprogramming and antitumor immunity have attracted much attention in cancer biology. Because it facilitates the cross-talk between ferroptosis and FA metabolism, ACSL4 is also a research hotspot in metabolic diseases and ischemia/reperfusion injuries. In this review, we focus on the structure, biological function, and unique role of ASCL4 in various human diseases. Finally, we propose that ACSL4 might be a potential therapeutic target.

Identification and verification of novel ferroptosis biomarkers predicts the prognosis of hepatocellular carcinoma

BACKGROUND

Big data mining and experiments are widely used to mine new prognostic markers.

METHODS

Candidate genes were identified from CROEMINE and FerrDb. Kaplan-Meier survival and Cox regression analysis were applied to assess the association of genes with Overall survival time (OS) and Disease-free survival time (DFS) in two HCC cohorts. Real-time quantitative polymerase chain reaction (RT-qPCR) and Immunohistochemistry were performed in HCC samples.

RESULTS

21 and 15 genes that can predict OS and DFS, which had not been reported before, were identified from 719 genes, respectively. Survival analysis showed elevated mRNA expression of GLMP, SLC38A6, and WDR76 were associated with poor prognosis, and three genes combination signature was an independent prognostic factor in HCC. RT-qPCR and Immunohistochemistry confirmed the results.

CONCLUSIONS

We established a novel computational process, which identified the expression levels of GLMP, SLC38A6, and WDR76 as potential ferroptosis-related biomarkers indicating the prognosis of HCC.

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

Background and Aims

The growing knowledge of ferroptosis has suggested the regulatory role of ferroptosis in hepatocellular carcinoma (HCC), but the pertinent molecular mechanisms remain unclear. Herein, this study investigated the mechanistic basis of ferroptosis-related genes (ferrGenes) in the growth of HCC.

Methods

Differentially expressed human ferrGenes and tumor-related transcription factors (TFs) were obtained from the The Cancer Genome Atlas (TCGA) dataset and the GTEx dataset. Spearman method-based correlation analysis were conducted to construct TF-ferrGene coexpression regulatory network. Key genes associated with prognosis were singled out with Lasso regression and multivariate Cox analysis to construct the prognostic risk model. Then the accuracy and independent prognostic ability of the model were evaluated. Expression of CENPA and STMN1 was determined in clinical HCC tissues and HCC cells, and their binding was analyzed with dual-luciferase and chromatin immunoprecipitation (ChIP) assays. Furthermore, ectopic expression and knockdown assays were performed in HCC cells to assess the effect of CENPA and STMN1 on ferroptosis and malignant phenotypes.

Results

The prognostic risk model constructed based on the eight TF-ferrGene regulatory network-related genes accurately predicted the prognosis of HCC patients. It was strongly related to the clinical characteristics of HCC patients. Moreover, CENPA/STMN1 might be a key TF-ferrGene regulatory network in ferroptosis of HCC. CENPA and STMN1 were overexpressed in HCC tissues and cells. Additionally, CENPA facilitated STMN1 transcription by binding to STMN1 promoter, thus facilitating the malignant phenotypes and suppressing the ferroptosis of HCC cells.

Conclusions

Taken together, CENPA curbs the ferroptosis of HCC cells by upregulating STMN1 transcription, thereby promoting HCC growth.

Identification of hepatocellular carcinoma-related subtypes and development of a prognostic model: a study based on ferritinophagy-related genes

BACKGROUND

Hepatocellular carcinoma still has a high incidence and mortality rate worldwide, and further research is needed to investigate its occurrence and development mechanisms in depth in order to identify new therapeutic targets. Ferritinophagy is a type of autophagy and a key factor in ferroptosis that could influence tumor onset and progression. Although, the potential role of ferritinophagy-related genes (FRGs) in liver hepatocellular carcinoma (LIHC) is unknown.

METHODS

Single-cell RNA sequencing (scRNA-seq) data of LIHC were obtained from the Gene Expression Omnibus (GEO) dataset. In addition, transcriptome and clinical follow-up outcome data of individuals with LIHC were extracted from the The Cancer Genome Atlas (TCGA) dataset. FRGs were collected through the GeneCards database. Differential cell subpopulations were distinguished, and differentially expressed FRGs (DEFRGs) were obtained. Differential expression of FRGs and prognosis were observed according to the TCGA database. An FRG-related risk model was constructed to predict patient prognosis by absolute shrinkage and selection operator (LASSO) and COX regression analyses, and its prognosis predictive power was validated. Ultimately, the association between risk score and tumor microenvironment (TME), immune cell infiltration, immune checkpoints, drug sensitivity, and tumor mutation burden (TMB) was analyzed. We also used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the expression of key genes in normal liver cells and liver cancer cells.

RESULTS

We ultimately identified 8 cell types, and 7 differentially expressed FRGs genes (ZFP36, NCOA4, FTH1, FTL, TNF, PCBP1, CYB561A3) were found among immune cells, and we found that Monocytes and Macrophages were closely related to FRGs genes. Subsequently, COX regression analysis showed that patients with high expression of FTH1, FTL, and PCBP1 had significantly worse prognosis than those with low expression, and our survival prediction model, constructed based on age, stage, and risk score, showed better prognostic prediction ability. Our risk model based on 3 FRGs genes ultimately revealed significant differences between high-risk and low-risk groups in terms of immune infiltration and immune checkpoint correlation, drug sensitivity, and somatic mutation risk. Finally, we validated the key prognostic genes FTH1, FTL, using qRT-PCR, and found that the expression of FTH1 and FTL was significantly higher in various liver cancer cells than in normal liver cells. At the same time, immunohistochemistry showed that the expression of FTH1, FTL in tumor tissues was significantly higher than that in para-tumor tissues.

CONCLUSION

This study identifies a considerable impact of FRGs on immunity and prognosis in individuals with LIHC. The collective findings of this research provide new ideas for personalized treatment of LIHC and a more targeted therapy approach for individuals with LIHC to improve their prognosis.

Identification of ferroptosis and drug resistance related hub genes to predict the prognosis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Currently, overcoming the drug resistance in HCC is a critical challenge and ferroptosis has emerged as a promising therapeutic option for cancer. We aim to construct a new gene signature related to ferroptosis and drug resistance to predict the prognosis in HCC. The RNA-seq data of HCC patients was obtained from the Cancer Genome Atlas database. Using least absolute shrinkage and selection operator cox regression, Kaplan-Meier analysis, and differential analysis, we constructed a prognostic model consisting of six hub genes (TOP2A, BIRC5, VEGFA, HIF1A, FTH1, ACSL3) related to ferroptosis and drug resistance in HCC. Functional enrichment, pathway enrichment and GSEA analysis were performed to investigate the potential molecular mechanism, and construction of PPI, mRNA-miRNA, mRNA-RBP, mRNA-TF and mRNA-drugs interaction networks to predict its interaction with different molecules. Clinical prognostic characteristics were revealed by univariate, multivariate cox regression analysis and nomogram. We also analyzed the relationship between the signature, immune checkpoints, and drug sensitivity. The expression of the gene signature was detected in HCC cell lines and HPA database. Our prognostic model classified patients into high and low-risk groups based on the risk scores and found the expression level of the genes was higher in the high-risk group than the low-risk group, demonstrating that high expression of the hub genes was associated with poor prognosis in HCC. ROC analysis revealed its high diagnostic efficacy in both HCC and normal tissues. The proportional hazards model and calibration analysis confirmed that the model's prediction was most accurate for 1- and 3-years survival. QRT-PCR showed the high expression level of the gene signature in HCC. Our study built a novel gene signature with good potential to predict the prognosis of HCC, which may provide new therapeutic targets and molecular mechanism for HCC diagnosis and treatment.

Ferroptosis: From Basic Research to Clinical Therapeutics in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and highly heterogeneous malignancies worldwide. Despite the rapid development of multidisciplinary treatment and personalized precision medicine strategies, the overall survival of HCC patients remains poor. The limited survival benefit may be attributed to difficulty in early diagnosis, the high recurrence rate and high tumor heterogeneity. Ferroptosis, a novel mode of cell death driven by iron-dependent lipid peroxidation, has been implicated in the development and therapeutic response of various tumors, including HCC. In this review, we discuss the regulatory network of ferroptosis, describe the crosstalk between ferroptosis and HCC-related signaling pathways, and elucidate the potential role of ferroptosis in various treatment modalities for HCC, such as systemic therapy, radiotherapy, immunotherapy, interventional therapy and nanotherapy, and applications in the diagnosis and prognosis of HCC, to provide a theoretical basis for the diagnosis and treatment of HCC to effectively improve the survival of HCC patients.

Identification and Validation of a Novel Prognostic Signature Based on Ferroptosis-Related Genes in Ovarian Cancer

BACKGROUND

Ovarian cancer is the most lethal gynecological tumor, with a poor prognosis due to the lack of early symptoms, resistance to chemotherapy, and recurrence. Ferroptosis belongs to the regulated cell death family, and is characterized by iron-dependent processes. Here, comprehensive bioinformatics analysis was applied to explore a valuable prognostic model based on ferroptosis-related genes, which was further validated in clinical OC samples.

METHODS

mRNA data of normal and ovarian tumor samples were obtained separately from the GTEx and TCGA databases. The least absolute shrinkage and selection operator (LASSO) cox regression was applied to construct the prognostic model based on ferroptosis-associated genes. Expression of ALOX12 in OC cell lines, as well as cell functions, including proliferation and migration, were examined. Finally, the prognostic efficiency of the model was assessed in the clinical tissues of OC patients.

RESULTS

A gene signature consisting of ALOX12, RB1, DNAJB6, STEAP3, and SELENOS was constructed. The signature divided TCGA, ICGC, and GEO cohorts into high-risk and low-risk groups separately. Receiver operating characteristic (ROC) curves and independent prognostic factor analysis were carried out, and the prognostic efficacy was validated. The expression levels of ALOX12 in cell lines were examined. Inhibition of ALOX12 attenuated cell proliferation and migration in HEY cells. Moreover, the prognostic value of ALOX12 expression was examined in clinical samples of OC patients.

CONCLUSION

This work constructed a novel ferroptosis-associated gene model. Furthermore, the clinical predictive role of ALOX12 was identified in OC patients, suggesting that ALOX12 might act as a potential prognostic tool and therapeutic target for OC patients.

Analysis of the potential association between ferroptosis and immune in hepatocellular carcinoma and their relationship with prognosis

Background

The development of targeted therapy and immunotherapy has enriched the treatment of hepatocellular carcinoma (HCC), however, have had poor or no reponse, or even no response. Previous research suggested that ferroptosis and tumor immune microenvironment (TIME) may have a fundamental impact on efficacy during HCC immunotherapy and targeted therapy. Therefore, there is a clinical need to develop a signature that categorizes HCC patients in order to make more accurate clinical decisions.

Methods

Clinical data and gene expression data of HCC patients were obtained from The Cancer Genome Atlas (TCGA) portal and International Cancer Genome Consortium (ICGC) portal. To identify ferroptosis-related immune-related genes (ferroptosis-related IRGs), Pearson correlation analysis was conducted. The ferroptosis-related IRGs prognostic signature (FIPS) was constructed using Univariate Cox and LASSO Cox algorithms. The predictive effectiveness of FIPS was evaluated using Receiver Operating Characteristic (ROC) curves and survivorship curve. The correlation ship between FIPS and TIME was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA) and CIBERSORT. The relationship between FIPS and immunotherapy responsiveness was evaluated using immunophenoscore. The expression level of 10 ferroptosis-related IRGs in normal liver tissues and HCC tissues was compared using immunohistochemistry. Finally, we established a nomogram (based on FIPS, TNM stage, and age) for clinical application.

Results

The FIPS was established with ten ferroptosis-related IRGs. The high-FIPS subgroup showed a poor clinical prognosis and an obviously higher proportion of HCC patients with advanced TNM stage, high WHO grade and high alpha fetoprotein(AFP) value. Analysis of TIME indicated that patients in the high-FIPS subgroup may be in immunosuppressed state. Meanwhile, we found that ferroptosis may be inhibited in the high-FIPS subgroup and this subgroup may be impervious to immunotherapy and sorafenib.

Conclusion

We constructed a novel potential prognostic signature for HCC patients that predicts overall survival, ferroptosis and immune status, sorafenib sensitivity, and immunotherapy responsiveness.

Identification of a Novel Ferroptosis-Related Gene Signature for Predicting Prognosis and Responsiveness to Immunotherapy in Hepatocellular Carcinoma

Purpose

Ferroptosis has been reported to regulate multiple biological behaviors. However, the prognostic and oncologic values of ferroptosis-related genes (FRGs) have not been comprehensively elucidated in hepatocellular carcinoma (HCC). Here, we aimed to construct FRGs-associated signature for stratification of the prognosis of HCC patients.

Methods

A list of FRGs was generated from FerrDb. Public databases were used to extract expression matrices and clinical information. TCGA cohort was randomly divided into a training set and a validation set. Prognostic signature for Overall Survival (OS) was established in training set and validated in internal cohorts (TCGA validation set and entire set) and external cohort (ICGC cohort). Additionally, the role of signature in HCC was well investigated by analysis of mutations, gene set enrichment analysis (GSEA), analysis of immune infiltrates, and analysis of response to immune checkpoint blockade (ICB) treatment. The oncogenic effects of ZFP69B on HCC were also investigated in vitro.

Results

We identified 12 FRGs-based signature for OS with LASSO regression. Patients were partitioned into different risk groups based on the signature. Overall, patients in different groups had different prognosis. The signature independently predicted OS in multivariate Cox regression analyses. Anti-tumor immune cells including activated CD8 T cells, cytolytic activity, and Th1 cells were negatively correlated with risk score in both TCGC and ICGC cohorts. Furthermore, low-risk patients responded better to ICB than high-risk patients. In addition, knockdown of ZFP69B reduced proliferation, migration, and invasion, and promoted erastin-induced ferroptosis of HCC cells.

Conclusion

We developed a prognostic signature based on FRGs to predict OS of HCC patients. And the signature may facilitate clinicians in identifying those who are likely to benefit from ICIs. The results also indicated that ZFP69B might regulate the process of ferroptosis and could be used as a novel potential target for HCC.

The Structure, Function and Regulation of Protein Tyrosine Phosphatase Receptor Type J and Its Role in Diseases

Protein tyrosine phosphatase receptor type J (PTPRJ), also known as DEP-1, HPTPη, or CD148, belongs to the R3 subfamily of receptor protein tyrosine phosphatases (RPTPs). It was first identified as an antioncogene due to its protein level being significantly downregulated in most epithelial tumors and cancer cell lines (e.g., colon, lung, thyroid, breast, and pancreas). PTPRJ regulates mouse optic nerve projection by inhibiting the phosphorylation of the erythropoietin-producing hepatocellular carcinoma (Eph) receptor and abelson murine leukemia viral oncogene homolog 1 (c-Abl). PTPRJ is crucial for metabolism. Recent studies have demonstrated that PTPRJ dephosphorylates JAK2 at positions Y813 and Y868 to inhibit leptin signaling. Akt is more phosphorylated at the Ser473 and Thr308 sites in Ptprj^-/- mice, suggesting that PTPRJ may be a novel negative regulator of insulin signaling. PTPRJ also plays an important role in balancing the pro- and anti-osteoclastogenic activity of the M-CSF receptor (M-CSFR), and in maintaining NFATc1 expression during the late stages of osteoclastogenesis to promote bone-resorbing osteoclast (OCL) maturation. Furthermore, multiple receptor tyrosine kinases (RTKs) as substrates of PTPRJ are probably a potential therapeutic target for many types of diseases, such as cancer, neurodegenerative diseases, and metabolic diseases, by inhibiting their phosphorylation activity. In light of the important roles that PTPRJ plays in many diseases, this review summarizes the structural features of the protein, its expression pattern, and the physiological and pathological functions of PTPRJ, to provide new ideas for treating PTPRJ as a potential therapeutic target for related metabolic diseases and cancer.

A five ferroptosis-related genes risk score for prognostic prediction of osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common bone cancer in adolescents, and has a high propensity to metastasize. Ferroptosis is a unique modality of cell death, driving the metastasis of cancer cells. Identifying ferroptosis-related genes (FRGs) as prognostic factors will be critical to predict the outcomes of OS. This study aimed to explore the prognostic value of FRGs in OS and build a prognostic model to indirectly improve OS patients' outcomes.

METHODS

OS data were downloaded from the TARGET database and 2 Gene Expression Omnibus datasets. Univariate Cox regression was conducted to assess FRGs. A risk score model basing on 5 FRGs was constructed via LASSO-Cox regression. Multivariate Cox regression analysis was used to determine the independent prognostic factors. The Nomogram model was built using independent prognostic factors. The relationship between the risk score and the immune cell infiltration was estimated by CIBERSORT, and the correlation between the risk score and immune checkpoints was also analyzed.

RESULTS

Based on the prognosis-related FRGs, we built a regression model: Risk score = (-0.01382853 × ACSL4) - (0.05371778 × HMOX1) - (0.02434655 × GPX4) - (0.16432810 × PRNP) - (0.15567120 × ATG7). OS patients with high risk score tended to suffer from poor prognosis, validated in 2 Gene Expression Omnibus datasets. The Nomogram model showed the combination of the risk score and the tumour-node-metastasis stage improved predictive effectiveness. The risk score was also related to immune cell infiltration and immune checkpoint expression.

CONCLUSION

The risk score model based on 5 FRGs was a reliable prognostic predictive indicator for OS patients.

Identification and validation of endocrine resistance-related and immune-related long non-coding RNA (lncRNA) signatures for predicting endocrinotherapy response and prognosis in breast cancer

Background

Endocrine resistance remains a major challenge in breast cancer (BRCA). Increasing evidence has revealed that long non-coding RNA (lncRNA) are closely implicated in tumorigenesis, drug resistance, and the immune-related pathways of cancer. However, the immune-related lncRNA remains to be thoroughly investigated in predicting the endocrine therapeutic response and prognosis of BRCA.

Methods

Based on the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, and calculating the correlation of lncRNAs with immune-related genes obtained from ImmPort and InnateDB databases, we finally obtained endocrine resistance-related and immune-related long non-coding RNAs (ERIR-lncRNAs). Univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression were performed to screen prognosis-associated ERIR-lncRNAs and establish signatures, using 2 separate datasets from GEO for external validation. Principal component analysis (PCA), Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and multivariate Cox regression were performed to demonstrate the robustness and predictability of the signature. We investigated tumor immune infiltration and tumor mutation burden (TMB) between high- and low-risk groups, and the role of key lncRNAs in endocrine resistant breast cancer was confirmed by quantitative real-time polymerase chain reaction (qRT-PCR), Cell Counting Kit 8 (CCK 8) and transwell assays.

Results

A total of 781 endocrine resistance related lncRNAs were identified, of which 12 lncRNAs were associated with immunity. Then, three ERIR-lncRNAs with prognostic relevance were screened to successfully construct the risk signature. Compared to sensitive patients, the endocrine resistant patients had higher risk scores in both the training and validation sets (P<0.05). The high-risk group had significantly shorter survival times (P<0.001) with area under the curve (AUC) values of 0.710, 0.649, and 0.672 at 1, 3, and 5 years. Univariate and multivariate Cox regression indicated that our signature was an independent prognostic factor (P<0.001). Through immune infiltration analysis, it was revealed that the high-risk scores were associated with T follicular helper (Tfh) differentiation and exhibited a pro-tumor phenomenon with the Th1/Th2 balance shifting toward Th2. The key lncRNAs promote cell proliferation and migration as confirmed by qRT-PCR, CCK-8 and transwell assays.

Conclusions

The ERIR-lncRNA signature is valuable in predicting endocrine therapeutic response and prognosis of BRCA, revealing a potential relationship between endocrine resistance and TME.

HSPB1 overexpression improves hypoxic-ischemic brain damage by attenuating ferroptosis in rats through promoting G6PD expression

Heat-shock protein B (HSPB1) has a neuroprotective effect on brain injury and is a negative regulator of ferroptosis. Therefore, we infer that HSPB1 plays a protective role in hypoxic-ischemic (HI) brain damage by inhibiting ferroptosis. A neonatal rat model of hypoxic-ischemic (HI) brain damage was established. HSPB1 overexpression plasmid and the negative control were injected into the lateral ventricle of rats 48 h before HI brain damage surgery. HSPB1 and glucose-6-phosphate dehydrogenase (G6PD) levels, infarction rate, iron accumulation, apoptosis, and ferroptosis-related markers were estimated with the assistance of qRT-PCR, 2,3,5-triphenyl tetrazolium chloride (TTC) staining, Prussian blue staining, iron assay kit, TUNEL staining, and Western blot. In vitro, after transfection, HSPB1 and G6PD levels, oxygen-glucose deprivation (OGD)-mediated hippocampal neuron cell viability, apoptosis, iron content, and ferroptosis-related markers were assessed using qRT-PCR, MTT, flow cytometry, iron assay kit, and Western blot. HSPB1 and G6PD were overexpressed in the hippocampus tissues of HI rats. High expression of HSPB1 in HI rats lessened infarction rate and ferritin level, hindered iron accumulation and apoptosis, and promoted GPX4, SLC7A11, and TFR1 levels. In OGD-mediated hippocampal neuron cells, HSPB1 upregulation intensified the viability and repressed apoptosis and ferroptosis, whereas G6PD silencing reversed the effects of HSPB1 upregulation. We documented that HSPB1 overexpression unleashes neuroprotective effects via modulating G6PD expression, which offers a novel target for the prevention and treatment of HI brain damage.NEW & NOTEWORTHY HSPB1 and G6PD were overexpressed in the hippocampus tissues of HI rats. High expression of HSPB1 in HI rats mitigated infarction rate and iron accumulation. HSPB1 overexpression reduced ferritin level, attenuated apoptosis, yet augmented GPX4, SLC7A11, and TFR1 levels in the hippocampus tissues of HI rats. G6PD deletion impaired the protective role of HSPB1 overexpression against HI brain damage-induced ferroptosis.

Identification and validation of immune and prognosis-related genes in hepatocellular carcinoma: A review

PURPOSE

Bioinformatics methods were used to identify the key genes associated with the immune microenvironment of hepatocellular carcinoma (HCC) to construct an immune risk prognostic model (IRPM) and to study the correlation between IRPM's risk groups and immune characteristics of patients with HCC.

METHODS

HCC transcriptome sequencing information was searched for immune-related genes (IRGs) that were regularly expressed in cancer tissues. The IRGs, which were strongly linked to overall survival were screened; the prognostic characteristics model was constructed using Cox regression analysis. IRPM's independent prognostic value was explored; Kaplan-Meier survival and receiver-operating characteristic curves were used to determine the model prediction ability in the led-to queue.

RESULTS

Patients in the high-risk group (HRG) showed significantly poor outcomes. Gene Set Enrichment Analysis revealed factors involved in both the HRG and low risk group. Immune-related hub genes (IRHGs) and drug sensitivity expression levels revealed that all IRHGs were correlated with drug sensitivity for certain chemotherapy drugs.

CONCLUSION

The study results may serve as a reference for improving prognosis, early screening, and immunotherapy in patients with HCC.

Ferroptosis-related differentially expressed genes serve as new biomarkers in ischemic stroke and identification of therapeutic drugs

Background

Iron is an essential nutrient element, and iron metabolism is related to many diseases. Ferroptosis is an iron-dependent form of regulated cell death associated with ischemic stroke (IS). Hence, this study intended to discover and validate the possible ferroptosis-related genes involved in IS.

Materials and methods

GSE16561, GSE37587, and GSE58294 were retrieved from the GEO database. Using R software, we identified ferroptosis-related differentially expressed genes (DEGs) in IS. Protein-protein interactions (PPIs) and enrichment analyses were conducted. The ROC curve was plotted to explore the diagnostic significance of those identified genes. The consistent clustering method was used to classify the IS samples. The level of immune cell infiltration of different subtypes was evaluated by ssGSEA and CIBERSORT algorithm. Validation was conducted in the test sets GSE37587 and GSE58294.

Results

Twenty-one ferroptosis-related DEGs were detected in IS vs. the normal controls. Enrichment analysis shows that the 21 DEGs are involved in monocarboxylic acid metabolism, iron ion response, and ferroptosis. Moreover, their expression levels were pertinent to the age and gender of IS patients. The ROC analysis demonstrated remarkable diagnostic values of LAMP2, TSC22D3, SLC38A1, and RPL8 for IS. Transcription factors and targeting miRNAs of the 21 DEGs were determined. Vandetanib, FERRIC CITRATE, etc., were confirmed as potential therapeutic drugs for IS. Using 11 hub genes, IS patients were categorized into C1 and C2 subtypes. The two subtypes significantly differed between immune cell infiltration, checkpoints, and HLA genes. The 272 DEGs were identified from two subtypes and their biological functions were explored. Verification was performed in the GSE37587 and GSE58294 datasets.

Conclusion

Our findings indicate that ferroptosis plays a critical role in the diversity and complexity of the IS immune microenvironment.

A multifaceted and feasible prognostic model of amino acid metabolism-related genes in the immune response and tumor microenvironment of head and neck squamous cell carcinomas

We investigated the role of amino acid metabolism (AAM) in head and neck squamous cell carcinoma (HNSCC) tissues to explore its prognostic value and potential therapeutic strategies. A risk score based on four AAM-related genes (AMG) was constructed that could predict the prognosis of HNSCC. These four genes were up-regulated in HNSCC tissues and might act as oncogenes. Internal validation in The Cancer Genome Atlas (TCGA) by bootstrapping showed that patients with high-risk scores had a poorer prognosis than patients with low-risk scores, and this was confirmed in the Gene Expression Omnibus (GEO) cohort. There were also differences between the high-risk and low-risk groups in clinical information and different anatomical sites such as age, sex, TNM stage, grade stage, surgery or no surgery, chemotherapy, radiotherapy, no radiotherapy, neck lymph node dissection or not, and neck lymphovascular invasion, larynx, overlapping lesion of lip, and oral cavity and pharynx tonsil of overall survival (OS). Immune-related characteristics, tumor microenvironment (TME) characteristics, and immunotherapy response were significantly different between high- and low-risk groups. The four AMGs were also found to be associated with the expression of markers of various immune cell subpopulations. Therefore, our comprehensive approach revealed the characterization of AAM in HNSCC to predict prognosis and guide clinical therapy.

A ferroptosis associated gene signature for predicting prognosis and immune responses in patients with colorectal carcinoma

Background: Colorectal carcinoma (CRC) is one of the most prevalent malignancies globally. Ferroptosis, a novel type of cell death, is critical in the development and treatment of tumors.

Objective: This study was designed to establish a genetic signature for ferroptosis which has a predictive effect on the outcomes and immunotherapeutic response of CRC.

Methods: Data of CRC patients were retrieved from TCGA and GEO databases. The genes associated with ferroptosis were obtained from GeneCards. The genetic signature for ferroptosis was identified by performing Cox regression analysis. Kaplan–Meier and ROC analysis were performed to assess the prognosis role of the genetic signature. CIBERSORT tool was used to identify a potential association of the genetic signature with the immune cells. The potential immunotherapeutic signatures and drug sensitivity prediction targeting this signature were also discussed. Immunohistochemistry was used to detect expression of ferroptosis-associated genes in CRC tissues and adjacent tissues.

Results: A ferroptosis-associated gene signature comprised of three genes (CDKN2A, FDFT1, and ACSL6) was developed for prediction of prognosis and evaluation of immune responses in CRC. Patients in the high-risk group tended to have a poor prognosis. In CRC, the ferroptosis-associated gene signature may function as independent predictors. Additionally, the expressional levels of the immune checkpoint proteins PD-L1 and CTLA-4 were substantially increased in the high-risk group. Moreover, we can distinguish between patients based on their immunotherapeutic responses more effectively if we categorize them by this signature. Additionally, candidate compounds were identified for the differentiation of CRC subtypes.

Conclusion: The ferroptosis-associated gene signature identified in this study is effective in predicting the prognosis and evaluating immunotherapeutic response in CRC patients, and provides us with novel insights into the potential effect of ferroptosis targeted treatment on CRC.

Ferroptosis regulators related scoring system by Gaussian finite mixture model to predict prognosis and immunotherapy efficacy in nasopharyngeal carcinoma

The role of ferroptosis in tumor progression and metastasis has been demonstrated. Nonetheless, potential biological function of ferroptosis regulatory pattern in nasopharyngeal carcinoma (NPC) remains unknown. Ferroptosis regulatory patterns of nasopharyngeal carcinoma samples were evaluated based on 113 ferroptosis regulators and three distinct ferroptosis subtypes were determined by unsupervised clustering. The ferroptosis score (FEP score) was identified to quantify ferroptosis patterns within individual tumors by Gaussian finite mixture model and systematically correlated with representative tumor characteristics. Subtype 1 and subtype 3 were consistent with immune activated phenotype, while subtype 2 was consistent with immune suppressed phenotype. High ferroptosis score, characterized by immune activation and suppression of mRNA based stemness index (mRNAsi) and Epstein-Barr virus (EBV) genes, indicated an immune activated tumor microenvironment (TME) phenotype, with better progression free survival (PFS) and lower risk of recurrence and metastasis. Low ferroptosis score, characterized by activation of Wnt and NF-κB signaling pathways and lack of effective immune infiltration, indicated an immune suppressed tumor microenvironment phenotype and poorer survival. High ferroptosis score was also correlated to enhanced response to immunotherapy, and was confirmed to correlate with therapeutic advantages and clinical benefits in an anti-programmed cell death 1 ligand 1 (PD-L1) immunotherapy cohort. As ferroptosis played a crucial role in the tumor microenvironment’s diversity, assessing the ferroptosis pattern within individual tumor with ferroptosis score could enhance our understanding of tumor microenvironment infiltration characterization and help develop more effective immunotherapy.

Perspectives and mechanisms for targeting ferroptosis in the treatment of hepatocellular carcinoma

Ferroptosis is a novel process of regulated cell death discovered in recent years, mainly caused by intracellular lipid peroxidation. It is morphologically manifested as shrinking of mitochondria, swelling of cytoplasm and organelles, rupture of plasma membrane, and formation of double-membrane vesicles. Work done in the past 5 years indicates that induction of ferroptosis is a promising strategy in the treatment of hepatocellular carcinoma (HCC). System xc^-/GSH/GPX4, iron metabolism, p53 and lipid peroxidation pathways are the main focus areas in ferroptosis research. In this paper, we analyze the ferroptosis-inducing drugs and experimental agents that have been used in the last 5 years in the treatment of HCC. We summarize four different key molecular mechanisms that induce ferroptosis, i.e., system xc^-/GSH/GPX4, iron metabolism, p53 and lipid peroxidation. Finally, we outline the prognostic analysis associated with ferroptosis in HCC. The findings summarized suggest that ferroptosis induction can serve as a promising new therapeutic approach for HCC and can provide a basis for clinical diagnosis and prevention of this disease.

Development and Validation of a Novel Mitochondrion and Ferroptosis-Related Long Non-Coding RNA Prognostic Signature in Hepatocellular Carcinoma

Mitochondrion and ferroptosis are related to tumorigenesis and tumor progression of hepatocellular carcinoma (HCC). Therefore, this study focused on exploring the participation of lncRNAs in mitochondrial dysfunction and ferroptosis using public datasets from The Cancer Genome Atlas (TCGA) database. We identified the mitochondrion- and ferroptosis-related lncRNAs by Pearson’s analysis and lasso-Cox regression. Moreover, real-time quantitative reverse transcription PCR (RT-qPCR) was utilized to further confirm the abnormal expression of these lncRNAs. Based on eight lncRNAs, the MF-related lncRNA prognostic signature (LPS) with outstanding stratification ability and prognostic prediction capability was constructed. In addition, functional enrichment analysis and immune cell infiltration analysis were performed to explore the possible functions of lncRNAs and their impact on the tumor microenvironment. The pathways related to G2M checkpoint and MYC were activated, and the infiltration ratio of regulatory T cells and M0 and M2 macrophages was higher in the high-risk group. In conclusion, these lncRNAs may affect mitochondria functions, ferroptosis, and immune cell infiltration in HCC through specific pathways, which may provide valuable insight into the progression and therapies of HCC.

The advanced development of molecular targeted therapy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC), one of the most common malignant tumors in China, severely threatens the life and health of patients. In recent years, precision medicine, clinical diagnoses, treatments, and innovative research have led to important breakthroughs in HCC care. The discovery of new biomarkers and the promotion of liquid biopsy technologies have greatly facilitated the early diagnosis and treatment of HCC. Progress in targeted therapy and immunotherapy has provided more choices for precise HCC treatment. Multiomics technologies, such as genomics, transcriptomics, and metabolomics, have enabled deeper understanding of the occurrence and development mechanisms, heterogeneity, and genetic mutation characteristics of HCC. The continued promotion and accurate typing of HCC, accurate guidance of treatment, and accurate prognostication have provided more treatment opportunities and prolonged survival timelines for patients with HCC. Innovative HCC research providing an in-depth understanding of the biological characteristics of HCC will be translated into accurate clinical practices for the diagnosis and treatment of HCC.

Prospective Analysis of Proteins Carried in Extracellular Vesicles with Clinical Outcome in Hepatocellular Carcinoma

Background: Extracellular vehicles (EVs) contain different proteins that relay information between tumor cells, thus promoting tumorigenesis. Therefore, EVs can serve as an ideal marker for tumor pathogenesis and clinical application. Objective: Here, we characterised EV-specific proteins in hepatocellular carcinoma (HCC) samples and established their potential protein-protein interaction (PPI) networks. Materials and Methods: We used multi-dimensional bioinformatics methods to mine a network module to use as a prognostic signature and validated the model's prediction using additional datasets. The relationship between the prognostic model and tumor immune cells or the tumor microenvironment status was also examined. Results: 1134 proteins from 316 HCC samples were mapped to the exoRBase database. HCC-specific EVs specifically expressed a total of 437 proteins. The PPI network revealed 321 proteins and 938 interaction pathways, which were mined to identify a three network module (3NM) with significant prognostic prediction ability. Validation of the 3NM in two more datasets demonstrated that the model outperformed the other signatures in prognostic prediction ability. Functional analysis revealed that the network proteins were involved in various tumor-related pathways. Additionally, these findings demonstrated a favorable association between the 3NM signature and macrophages, dendritic, and mast cells. Besides, the 3NM revealed the tumor microenvironment status, including hypoxia and inflammation. Conclusion: These findings demonstrate that the 3NM signature reliably predicts HCC pathogenesis. Therefore, the model may be used as an effective prognostic biomarker in managing patients with HCC.

Integrated Analysis Reveals Critical Ferroptosis Regulators and FTL Contribute to Cancer Progression in Hepatocellular Carcinoma

Background: The carcinogenesis and prognosis of hepatocellular carcinoma (HCC) involve complex molecular mechanisms, and ferroptosis is related to the development and therapeutic efficacy of HCC, but the specific mechanism and prognostic role of ferroptosis-related genes in HCC have not been elucidated. Methods: Differentially expressed gene analysis, Cox regression, and unsupervised consensus clustering were applied to identify crucial ferroptosis regulators and establish ferroptosis-related subtypes in HCC. Random forest analysis and survival analysis were adopted to confirm FTL as the hub prognostic and diagnostic ferroptosis regulator in HCC. Results: The ferroptosis-related subtypes based on the crucial prognostic ferroptosis regulators showed that patients in fescluster A had a higher survival probability (p < 0.001) and better clinical characteristics than patients in fescluster B in the TCGA-LIHC cohort. Patients with a high tumor mutation burden (TMB) in fescluster B presented a significantly poorer prognosis. FTL was the core ferroptosis regulator, and its low expression revealed a significant survival advantage compared with its high expression (p = 0.03). The expression and predictive value of FTL were both closely related to the clinical features (p < 0.05). Expression of FTL accurately distinguished HCC from normal tissues in the TCGA-LIHC cohort, ICGC cohort, and GSE14520 dataset. In addition, higher infiltrating fractions of immune cells, such as activated CD8⁺ T cells and Gamma delta T cells, mainly enriched immune-related signaling pathways, including the IL2-STAT3 signaling pathway and interferon-gamma response signaling pathway, and higher expression of immune checkpoints, including PDCD1, CTLA4, TIGIT, and CD83, were presented in patients with high FTL expression (p < 0.05). Patients with high FTL were more sensitive to some targeted drugs, such as cisplatin, dasatinib, and sorafenib, than those with low FTL (p < 0.05). A nomogram based on FTL accurately predicted the prognosis of HCC. Further knockdown of FTL was determined to significantly inhibit cell proliferation and migration in HCC. Conclusion: Our study validated ferroptosis-related subtypes and FTL with effective prognostic value in HCC and was beneficial for identifying candidates suitable for targeted drug therapy and immunotherapy, thereby offering further insight into individual treatment strategies to improve disease outcomes in HCC patients.

Construction and Validation of a 6-Ferroptosis Related Gene Signature for Prognosis and Immune Landscape Prediction in Melanoma

Ferroptosis is a newly discovered form of non-apoptotic cell death that relies on iron-mediated oxidative damage, playing a crucial role in the progression and therapy resistance of melanoma. Hence, the potential value of ferroptosis-related genes (FRGs) as a prognostic model and therapeutic target in melanoma requires further investigation. In this study, the relationship between FRGs and melanoma was revealed by analyzing the mRNA expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Synthesis (GEO). A 6-FRGs signature was constructed by Univariate, multivariate, and lasso Cox regression analyses in the TCGA cohort. The GEO database was used to validate the efficacy of the signature. The protein and mRNA expression level of the signature genes were examined in real-world melanoma tissues via immunohistochemical and quantificational real-time polymerase chain reaction (qRT-PCR). Functional enrichment analysis and immune-related analysis were conducted to identify the potential biological functions and pathways of the signature. Ten putative small molecule drugs were predicted by Connectivity Map (CMAP). As a result, a 6-FRGs signature was constructed to stratify melanoma patients into two risk groups. Compared with the low-risk group, patients in the high-risk group had a worse prognosis and a lower ImmuneScore. Immune-related pathways were enriched in the low-risk group. Immune Function and immune cell infiltration of the low-risk group were significantly higher than that of the high-risk group. The differential expression of these six FRGs in melanoma and adjacent normal tissues was confirmed. Moreover, higher expression of immune checkpoint molecules and a greater sensitivity to immunotherapy were observed in the low-risk group. Some small molecular drugs in the CMAP database hold the potential to treat melanoma. Overall, we identified a novel FRGs signature for prognostic prediction in melanoma. Based on the signature-related immune infiltration landscape found in our study, targeting the FRGs might be a therapeutic alternative for melanoma.

A Novel Predictive Model for Adrenocortical Carcinoma Based on Hypoxia- and Ferroptosis-Related Gene Expression

Background

The impact of hypoxia on ferroptosis is important in cancer proliferation, but no predictive model combining hypoxia and ferroptosis for adrenocortical carcinoma (ACC) has been reported. The purpose of this study was to construct a predictive model based on hypoxia- and ferroptosis-related gene expression in ACC.

Methods

We assessed hypoxia- and ferroptosis-related gene expression using data from 79 patients with ACC in The Cancer Genome Atlas (TCGA). Then, a predictive model was constructed to stratify patient survival using least absolute contraction and selection operation regression. Gene expression profiles of patients with ACC in the Gene Expression Omnibus (GEO) database were used to verify the predictive model.

Results

Based on hypoxia-related gene expression, 79 patients with ACC in the TCGA database were divided into three molecular subtypes (C1, C2, and C3) with different clinical outcomes. Patients with the C3 subtype had the shortest survival. Ferroptosis-related genes exhibited distinct expression patterns in the three subtypes. A predictive model combining hypoxia- and ferroptosis-related gene expression was constructed. A nomogram was constructed using age, sex, tumor stage, and the predictive gene model. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the gene signature was mainly related to the cell cycle and organelle fission.

Conclusion

This hypoxia-and ferroptosis-related gene signature displayed excellent predictive performance for ACC and could serve as an emerging source of novel therapeutic targets in ACC.

A novel ferroptosis-related gene signature for clinically predicting recurrence after hepatectomy of hepatocellular carcinoma patients

High recurrence rate in HCC is the primary cause of the poor prognosis after hepatectomy. Therefore, in this study, we aimed to construct a gene signature for predicting the recurrence rate in HCC. The mRNA expression profiles and clinical information of HCC patients from GEO and TCGA databases were used, and ferroptosis-related gene list was obtained from the FerrDb database. We identified 39 ferroptosis-related genes (FDEGs) that were differentially expressed between HCC samples and normal tissues from the GSE14520 dataset. The univariate and multivariate Cox regression analyses were employed to construct a prognostic signature. Seven FDEGs (MAPK9, SLC1A4, PCK2, ACSL3, STMN1, CDO1, and CXCL2) were included to construct a risk model, which was validated in the TCGA dataset. Patients in high-risk groups exhibited a significantly poor prognosis compared with patients in low-risk groups in both the training set (GSE14520 cohort) and the validation set (TCGA cohort). Multivariate cox regression analyses demonstrated that the 7-gene signature was an independent risk factor for RFS in HCC patients. KEGG analysis showed that FDEGs were mainly enriched in Ferroptosis, Hepatocellular carcinoma pathway, and MAPK signaling pathway. GSEA analysis suggested that the high-risk group was correlated with multiple oncogenic signatures and invasive-related pathways. These results indicated that this risk model can accurately predict recurrence after hepatectomy and offer novel research directions for personalized treatment in HCC patients.

Constructing an immune- and ferroptosis-related lncRNA signature to predict the immune landscape of human bladder cancer

Background

LncRNAs play a variety of roles in the tumor microenvironment and cancer immune responses. Determining the significance of bladder cancer (BLCA)‐related genes to predict the prognostic and therapeutic response of BLCA is important.

Methods

IrlncRNA/ frlncRNA pairs were determined using univariate analysis. The signature was constructed based on this pairs. Finally, analysis and internal validation were performed from several aspects.

Results

We identified 60 immune‐ and ferroptosis‐related lncRNA pairs, among which 12 were included in the Cox proportional hazards model. Patients in low‐risk group survived for significantly longer. Survival and riskScore analyses showed that the low‐risk group had a significantly better clinical outcome. ROC curve analysis showed that AUC of OS values were more than 0.75 in the training set and the whole cohort. As assessed using Cox analysis, the riskScore was an independent prognostic predictor in the training, testing set and the whole cohort. The areas under the multi‐index ROC in the training set, the testing set, and the whole cohort were 0.777, 0.692, and 0.748, respectively. High‐risk group was positively associated with most of tumor‐infiltrating immune cells. High‐risk Scores correlated positively with high expression of CD274, but not with PD‐1. Low riskScores correlated positively with high expression levels of the genes ERBB2 and nectin‐4. High‐risk Score was associated with a lower IC50 value for Docetaxel, cisplatin, and Pazopanib, while there was an opposite result for metformin.

Conclusions

The signature constructed by pairing irlncRNAs and frlncRNAs showed a notable clinical predictive value.

Identification of a pyroptosis-related lncRNA risk model for predicting prognosis and immune response in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is one of the most common malignant tumors and is diagnosed at an advanced stage with a poor prognosis worldwide. Pyroptosis is involved in the initiation and progression of tumors. This research focused on constructing a pyroptosis-related ceRNA network to generate a reliable risk model for risk prediction and immune infiltration analysis of COAD.

Methods

Transcriptome data, miRNA-sequencing data, and clinical information were downloaded from the TCGA database. First, differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs) were identified to construct a pyroptosis-related ceRNA network. Second, a pyroptosis-related lncRNA risk model was developed applying univariate Cox regression analysis and least absolute shrinkage and selection operator method (LASSO) regression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were utilized to functionally annotate RNAs contained in the ceRNA network. In addition, Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, univariate and multivariate Cox regression, and nomogram were applied to validate this risk model. Finally, the relationship of this risk model with immune cells and immune checkpoint blockade (ICB)-related genes was analyzed.

Results

A total of 5373 DEmRNAs, 1159 DElncRNAs, and 355 DEmiRNAs were identified. A pyroptosis-related ceRNA regulatory network containing 132 lncRNAs, 7 miRNAs, and 5 mRNAs was constructed, and a ceRNA-based pyroptosis-related risk model including 11 lncRNAs was built. The tumor tissues were classified into high- and low-risk groups according to the median risk score. Kaplan-Meier analysis showed that the high-risk group had a shorter survival time; ROC analysis, independent prognostic analysis, and nomogram further indicated the risk model was a significant independent prognostic factor what had an excellent ability to predict patients’ risk. Moreover, immune infiltration analysis indicated that the risk model was related to immune infiltration cells (i.e., B cell naïve, T cell follicular helper, macrophage M1) and ICB-related genes (i.e., PD-1, CTLA4, HAVCR2).

Conclusions

This pyroptosis-related lncRNA risk model possessed good prognostic value, and the ability to predict the outcome of ICB immunotherapy in COAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02572-8.

Prognostic and therapeutic significance of a novel ferroptosis related signature in colorectal cancer patients

Increasing studies have highlighted the importance of ferroptosis in colorectal cancer (CRC). However, how to use ferroptosis-related genes (FRGs) to predict the prognosis and guide the treatment of CRC remains unknown. To build a prognostic prediction model using the GEO and TCGA databases and explored a therapeutic strategy for CRC patients based on FRGs. A total of 60 FRGs were identified and three of them including ACACA, GSS, and NFS1 were associated with the prognosis of CRC. Using Lasso regression analysis, an FRGs signature was constructed and validated as an independent prognostic predictor. Then we developed a nomogram based on the FRGs signature and clinical prognostic factors to predict the prognosis of CRC patients, which was better than the traditional TNM staging system. Single-sample gene set enrichment analysis (ssGSEA) was further performed for the functional analysis and suggested that JAK-STAT signaling, Ras signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway were significantly enriched in CRC patients with higher FRGs risk score. Interestingly, CRC cells with higher FRGs risk score were more sensitive to RSL3. Knocking down GSS and NFS1 increased the FRGs risk score and the sensitivity of CRC cells to RSL3. For the clinic use, we screened 75 FDA-approved cancer drugs and found that Fludarabine phosphate could decrease the expression of GSS and NFS1 most. Fludarabine phosphate, in combination with RSL3, showed a strong synergistic effect on CRC cells. Together, this study identified a potent prognostic model and provided an alternative individualized treatment for CRC patients.

Identification and validation of the high expression of pseudogene TCAM1P in cervical cancer via integrated bioinformatics analysis

Background

HPV as the main cause of cervical cancer has long been revealed, but the detailed mechanism has not yet been elucidated. The role of testis/cancer antigen in cervical cancer has been revealed. However, there are no reports about the statement of testis/cancer-specific non-coding RNA. In this study, we first proposed TCAM1P as a testis/cancer-specific pseudogene, and used a series of experimental data to verify its relationship with HPV, and analyzed its diagnosis value of high-grade cervical lesions and the mechanism of their high expression in cervical cancer. This provides a new direction for the prevention and treatment of cervical cancer.

Methods

The specific expression of pseudogenes in each tissue was calculated by “TAU” formula. ROC curve was used to judge the diagnosed value of TCAM1P for high-grade lesions. The proliferation ability of cells was measured by CCK8. The expression of TCAM1P, HPV E6/E7 were detected by qRT-PCR. The binding for RBPs on TCAM1P was predicted by starbase v2.0 database, then RIP assay was used to verify. Besides, Gene Ontology (GO) and KEGG enrichment analysis were performed with “clusterprofiler” R package.

Results

TCAM1P was specifically high-expressed in normal testicular tissue and cervical cancer. Interesting, with the severity of cervical lesions increased, the expression of TCAM1P increased, and TCAM1P could effectively diagnose high-grade cervical lesions. Besides, the expression of TCAM1P was HPV dependent, with highest expression in HPV-positive cervical cancer tissues. Furthermore, RIP assay showed that EIF4A3 regulated the expression of TCAM1P through binding with it. CCK8 assay showed that TCAM1P promoted the proliferation and the Gene ontology (GO) and KEGG Pathway enrichment analysis same suggested that TCAM1P is involved in multiple ways in cell proliferation including Cell cycle, DNA replication and etc.

Conclusions

In this study, we firstly proposed that TCAM1P is cancer/testis pseudogene and is regulated by HPV E6/E7 and EIF4A3. TCAM1P promotes the proliferation of cervical cancer cells and acts as promoter in cervical cancer. Otherwise, TCAM1P promote proliferation through regulating cell cycle and DNA replication, but more evidence needs to be provided to reveal the mechanism by which TCAM1P plays a role in cervical cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02440-7.

Comprehensive Analysis of Ferroptosis-Related Markers for the Clinical and Biological Value in Gastric Cancer

Gastric cancer is a highly malignant tumor with poor survival rate. Ferroptosis, a newly defined regulated cell death, is closely related to several tumors. Introduction of ferroptosis is promising for cancer treatments. However, the predictive role of ferroptosis in GC remains elusive. In this study, we screened the ferroptosis-related genes which were differentially expressed between normal and GC tissues. Then, based on these differentially expressed genes (DEGs), the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regressions were applied to construct the 10-gene prognostic signature (SP1, MYB, ALDH3A2, KEAP1, AIFM2, ITGB4, TGFBR1, MAP1LC3B, NOX4, and ZFP36) in TCGA training dataset. Based on the median risk score, all GC patients in TCGA training dataset and GSE84437 testing dataset were classified into a high- or low-risk group. GC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P < 0.001). Combined with the clinical characteristics, the risk score was proven as an independent factor for predicting the OS of GC patients. Besides, the GC patients in the high- or low-risk group showed significantly different GO and KEGG functional enrichments, somatic mutation, fractions of immune cells, and immunotherapy response. Then, the expression levels of these genes in signature were further verified in the GC cell lines and our own GC samples (30-paired tumor/normal tissues). Furthermore, the effects of ferroptosis inducer Erastin on these 10 ferroptosis-related genes in GC cell lines were also explored in our study. In conclusion, our study constructed a prognostic signature of 10 ferroptosis-related genes, which could well predict the prognosis and immunotherapy for GC patients.

Ferroptosis-Associated Classifier and Indicator for Prognostic Prediction in Cutaneous Melanoma

Ferroptosis plays a critical role in different types of cancers, but the prognostic impact of ferroptosis in cutaneous melanoma remains lacking. Therefore, ferroptosis-related genes (FRGs) were firstly obtained from the FerrDb database and the differentially expressed FRGs were identified by the “limma” algorithm. Next, the prognostic differentially expressed FRGs were screened out by univariate Cox regression, which were subsequently used to cluster melanomas into two subtypes (clusters A and B). Besides, the Boruta algorithm and principal component analysis (PCA) were performed to build a 15-FRGs indicator, which can robustly predict patients' overall survival (OS) and be considered as an independent prognostic factor in melanoma. The melanoma patients were further divided into high- and low-FRGs score groups. The high score group have a good prognosis, with higher T cell immune infiltrating and lower mutation frequencies in NRAS, KRAS, and NF1. Finally, we discovered that many immune processes and several chemotherapy drugs were closely associated with FRGs score. Thus, our study provides a novel ferroptosis-associated classifier and indicator to predict the prognosis of melanoma. Besides, we identified several potential chemotherapy drugs to induce ferroptosis and could supply additional effective treatments.

Bioinformatics Identification of Ferroptosis-Related Biomarkers and Therapeutic Compounds in Ischemic Stroke

Background: Stroke is one of the most common deadly diseases with an estimated 780,000 new cases globally, of which ischemic stroke accounts for over 80% of all cases. Ferroptosis is a new form of programmed cell death that plays a vital role in many diseases, including ischemic stroke and heart diseases. The role of the ferroptosis-related gene in the diagnosis, prognosis, or therapy of ischemic stroke was not fully clarified.

Methods: Ferroptosis-related differentially expressed genes (DEGs) in ischemic stroke were identified by bioinformatic analysis of the GSE16561 and GSE22255 datasets. Subsequently, receiver operator characteristic (ROC) monofactor analysis was performed to evaluate the diagnostic value of ferroptosis-related biomarkers in ischemic stroke.

Results: A total of 10 ferroptosis-related DEGs were identified in ischemic stroke vs. normal control. GO and KEGG analysis revealed that these 10 ferroptosis-related DEGs were mainly enriched in response to oxidative stress, HIF-1 signaling pathway, ferroptosis, lipid, and atherosclerosis. Moreover, the random forest model suggested three ferroptosis-related biomarkers, namely, PTGS2, MAP1LC3B, and TLR4, for ischemic stroke. Interestingly, the expression of PTGS2, MAP1LC3B, and TLR4 was upregulated in ischemic stroke. ROC monofactor analysis demonstrated a good performance of MAP1LC3B, PTGS2, and TLR4 in the diagnosis of ischemic stroke. The expression and diagnostic value of MAP1LC3B, PTGS2, and TLR4 in ischemic stroke were also verified using GSE22255. We also revealed the transcription factor regulation network and co-expressed protein network of ferroptosis-related biomarkers. Several potential therapeutic compounds corresponding to MAP1LC3B, PTGS2, and TLR4 were also identified for ischemic stroke, including Zinc12503187 (Conivaptan), Zinc3932831 (Avodart), Zinc64033452 (Lumacaftor), Zinc11679756 (Eltrombopag), Zinc100378061 (Naldemedine), and Zinc3978005 (Dihydroergotamine).

Conclusion: Our results suggested MAP1LC3B, PTGS2, and TLR4 as potential diagnostic biomarkers for ischemic stroke, providing more evidence about the vital role of ferroptosis in ischemic stroke.

Heat Shock Protein Beta 1 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most serious malignancies. The main features of HCC are vascular invasion and drug resistance. Ferroptosis is a novel cell program that is involved in several diseases, such as cancer. Heat shock protein beta 1 (HSPB1) is a major component of heat shock proteins. A recent study showed that HSPB1 could be a new therapeutic target for colorectal cancer with 5-fluorouracil-acquired resistance. However, the functional role of HSPB1 in HCC remains unclear.

Aim

The aim of this study is to clarify HSPB1 expression in HCC and its potential therapeutic and prognostic value.

Methods

We collected data on HSPB1 expression levels in HCC and normal liver tissues from The Cancer Genome Atlas and Gene Expression Omnibus databases. We then validated it using immunohistochemistry (IHC). Receiver operating characteristic and Kaplan–Meier survival curves were used to investigate the role of HSPB1 in the prognosis analysis of HCC. Further, we used the online Search Tool for the Retrieval of Interacting Genes/Proteins website, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes to conduct enrichment analysis and identify the predictive signaling pathways. Meanwhile, we used the TIMER and GSVA package of R (v3.6.3) to analyze the association between HSPB1 and immunocyte infiltration.

Results

Compared to normal tissues, there was differential expression of HSPB1 in pan-cancers. HSPB1 expression was higher in HCC tissues than in normal tissues (p<0.05). There was an evident significant difference between HSPB1 mRNA levels and histologic grade, vascular invasion, and alpha-fetoprotein level (all p values<0.05). Univariate analysis indicated that HCC patients with high HSPB1 levels had shorter overall survival rates than those with low HSPB1 levels (p<0.05). MAPK14, HSPA8, MAPKAPK3, MAPKAPK5, and MAPKAPK2 are essential proteins that interact with HSPB1. There was a significant correlation between HSPB1 expression levels and immune cell infiltration, including CD4⁺ T cells (r=0.203, p<0.05).

Conclusion

High HSPB1 expression is closely associated with a worse prognosis in HCC patients, and HSPB1 may be a target of immunotherapy in HCC.

Ferroptosis-related gene signature associates with immunity and predicts prognosis accurately in patients with osteosarcoma

Osteosarcoma has been the most common malignant bone tumor in children and adolescents, while the 5‐y survival of osteosarcoma patients gained no significant improvement over the past decades. This study aimed to explore the role of ferroptosis‐related genes (FRGs) in the development and prognosis of osteosarcoma. The datasets of osteosarcoma patients including RNA sequencing data and clinical information were acquired from the TRGET and Gene Expression Omnibus (GEO) databases. The identification of molecular subgroups with different FRG expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. The prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis. The ESTIMATE algorithm was applied for determining the stromal score, immune score, ESTIMA score, and tumor purity of osteosarcoma patients. Functional analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were conducted to explore the underlying mechanisms in the development and prognosis of osteosarcoma. Two molecular subgroups with different FRGs expression patterns were identified. The molecular subgroups with higher immune score and more active immune status showed better prognostic survival. On the basis of FRGs, a prognostic model and a nomogram integrating clinical characteristics were constructed and their prediction efficiency for osteosarcoma prognosis were well validated. Gene functional enrichment analysis showed that these differentially expressed FRGs were mainly enriched in immunity‐related signaling pathways, indicating that FRGs may affect the development and prognosis of osteosarcoma by regulating the immune microenvironment. The expression profiles of FRGs were closely related to the immunity status and prognostic survival of osteosarcoma patients. The interaction between ferroptosis and immunity in the development of osteosarcoma could provide a new insight into the exploration of molecular mechanisms and targeted therapies of osteosarcoma patients.

A Ferroptosis-Related Gene Model Predicts Prognosis and Immune Microenvironment for Cutaneous Melanoma

Background

Cutaneous melanoma is a common but aggressive tumor. Ferroptosis is a recently discovered cell death with important roles in tumor biology. Nevertheless, the prognostic power of ferroptosis-linked genes remained unclear in cutaneous melanoma.

Methods

Cutaneous melanoma patients of TCGA (The Cancer Genome Atlas) were taken as the training cohort while GSE65904 and GSE22153 as the validation cohorts. Multifactor Cox regression model was used to build a prognostic model, and the performance of the model was assessed. Functional enrichment and immune infiltration analysis were used to clarify the mechanisms.

Results

A five ferroptosis-linked gene predictive model was developed. ALOX5 and GCH1 were illustrated as independent predictive factors. Functional assessment showed enriched immune-linked cascades. Immune infiltrating analysis exhibited the distinct immune microenvironment.

Conclusion

Herein, a novel ferroptosis-related gene prognostic model was built in cutaneous melanoma. This model could be used for prognostic prediction, and maybe helpful for the targeted and immunotherapies.

Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma

Purpose

Ferroptosis, as a novel regulated cell death form, has a close interaction with metabolism, which is largely unknown in cancer. In the present study, we conducted a comprehensive analysis of ferroptosis-related metabolic genes to delineate the metabolic signatures induced by ferroptosis and evaluate its prognostic significance in hepatocellular carcinoma (HCC).

Methods

The ferroptosis-related metabolic genes (Fer-MRGs) were identified by correlation analyses with transcriptome data from The Cancer Genome Atlas and Gene Expression Omnibus. Then, univariate and the least absolute shrinkage and selection operator Cox regression analysis was used to establish a novel risk score model. Univariate and multivariate COX analyses were used to identify independent prognostic factors for overall survival (OS) of HCC, and a nomogram was developed. The Fer-MRGs’ expression was further evaluated by quantitative real-time polymerase chain reaction in HCC.

Results

A total of 77 metabolic genes were identified as Fer-MRGs, and 26 were found with prognostic values for OS of HCC. Then, a novel nine-gene (AKR1C3, ATIC, G6PD, GMPS, GNPDA1, IMPDH1, PRIM1, RRM2, and TXNRD1) risk score model was constructed. Survival analyses showed worse OS in high-risk patients both in the training and validation groups. The model was also identified as an independent prognostic factor for HCC, and a prognostic nomogram for OS was further established with superior discriminative capacity and prediction accuracy. Notably, close correlations were also identified between the risk score and the expression of immune checkpoint genes, immune subtypes of tumor, and susceptibility of HCC to chemotherapeutic agents. Finally, elevated expression of eight Fer-MRGs (except for IMPDH1) was further verified in 16 pairs of HCC tumor and adjacent tissues.

Conclusion

These results indicated the intense interaction between ferroptosis and metabolism, the significant role of ferroptosis-related MRGs, and the great potential of the novel risk score model for prognosis prediction in HCC.

A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer

Background

Colon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients.

Methods

Alteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features.

Results

The prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient.

Conclusion

The novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.

An Original Ferroptosis-Related Gene Signature Effectively Predicts the Prognosis and Clinical Status for Colorectal Cancer Patients

Background

Colorectal cancer (CRC) is one of the most common malignant tumors in the world. Ferroptosis is a newly defined form of cell death, distinguished by different morphology, biochemistry, and genetics, and involved in CRC progression and treatment. This study aims to establish a predictive model to elucidate the relationship between ferroptosis and prognosis of CRC patients, to explore the potential value of ferroptosis in therapeutic options.

Methods

The ferroptosis-related genes were obtained from the GeneCards and FerrDb websites. The limma R package was used to screen the differential ferroptosis-related genes (DEGs) in CRC from The Cancer Genome Atlas (TCGA) dataset. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regressions were to establish the 10-gene prognostic signature. The survival and receiver operating characteristic (ROC) curves were illustrated to evaluate the predictive effect of the signature. Besides, independent prognostic factors, downstream functional enrichment, drug sensitivity, somatic mutation status, and immune feature were analyzed. Moreover, all these conclusions were verified by using multiple datasets in International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO).

Results

Ten ferroptosis-related gene signature (TFAP2C, SLC39A8, NOS2, HAMP, GDF15, FDFT1, CDKN2A, ALOX12, AKR1C1, ATP6V1G2) was established to predict the prognosis of CRC patients by Lasso cox analysis, demonstrating a good performance on Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) analyses. The CRC patients in the high- or low-risk group showed significantly different fractions of immune cells, such as macrophage cells and CD8+ T cells. Drug sensitivity and somatic mutation status like TP53 were also closely associated with the risk scores.

Conclusions

In this study, we identified a novel ferroptosis-related 10-gene signature, which could effectively predict the prognosis and survival time of CRC patients, and provide meaningful clinical implications for targeted therapy or immunotherapy. Targeting ferroptosis is a good therapeutic option for CRC patients. Further studies are needed to reveal the underlying mechanisms of ferroptosis in CRC.

Identification of a Ferroptosis-Related LncRNA Signature as a Novel Prognosis Model for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a highly heterogeneous malignancy, which makes prognosis prediction of LUAD very challenging. Ferroptosis is an iron-dependent cell death mechanism that is important in the survival of tumor cells. Long non-coding RNAs (lncRNAs) are considered to be key regulators of LUAD development and are involved in ferroptosis of tumor cells, and ferroptosis-related lncRNAs have gradually emerged as new targets for LUAD treatment and prognosis. It is essential to determine the prognostic value of ferroptosis-related lncRNAs in LUAD. In this study, we obtained RNA sequencing (RNA-seq) data and corresponding clinical information of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and ferroptosis-related lncRNAs by co-expression analysis. The best predictors associated with LUAD prognosis, including C5orf64, LINC01800, LINC00968, LINC01352, PGM5-AS1, LINC02097, DEPDC1-AS1, WWC2-AS2, SATB2-AS1, LINC00628, LINC01537, LMO7DN, were identified by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, and the LUAD risk prediction model was successfully constructed. Kaplan-Meier analysis, receiver operating characteristic (ROC) time curve analysis and univariate and multivariate Cox regression analysis and further demonstrated that the model has excellent robustness and predictive ability. Further, based on the risk prediction model, functional enrichment analysis revealed that 12 prognostic indicators involved a variety of cellular functions and signaling pathways, and the immune status was different in the high-risk and low-risk groups. In conclusion, a risk model of 12 ferroptosis related lncRNAs has important prognostic value for LUAD and may be ferroptosis-related therapeutic targets in the clinic.

Biomarkers in Hepatobiliary Cancers: What is Useful in Clinical Practice?

Hepatocellular carcinoma (HCC) and biliary tract cancers (BTC) exhibit a poor prognosis with 5-year overall survival rates around 15%, all stages combined. Most of these primary liver malignancies are metastatic at diagnostic, with only limited therapeutic options, relying mainly on systemic therapies. Treatment modalities are different yet partially overlapping between HCC and BTC. The complex molecular profile of BTC yields to several actionable therapeutic targets, contrary to HCC that remains the field of antiangiogenic drugs in non-molecularly selected patients. Immunotherapy is now validated in the first line in HCC in combination with bevacizumab, while clinical activity of single agent immunotherapy appears limited to a subset of patients in BTC, still poorly characterized, and combinations are currently under investigation. In this review, we provide a critical evaluation and grading of clinical relevance on (i) the main prognostic biomarkers in HCC and BTC, (ii) the main theragnostic biomarkers in both tumors, and lastly (iii) what is recommended in clinical practice.