Ferroptosis-related genes are potential prognostic molecular markers for patients with colorectal cancer

Exploring Predictive and Prognostic Biomarkers in Colorectal Cancer: A Comprehensive Review

Colorectal cancer (CRC) remains the second leading cause of cancer-related mortality worldwide. While immune checkpoint inhibitors have significantly improved patient outcomes, their effectiveness is mostly limited to tumors with microsatellite instability (MSI-H/dMMR) or an increased tumor mutational burden, which comprise 10% of cases. Advancing personalized medicine in CRC hinges on identifying predictive biomarkers to guide treatment decisions. This comprehensive review examines established tissue markers such as KRAS and HER2, highlighting their roles in resistance to anti-EGFR agents and discussing advances in targeted therapies for these markers. Additionally, this review summarizes encouraging data on promising therapeutic targets and highlights the clinical utility of liquid biopsies. By synthesizing current evidence and identifying knowledge gaps, this review provides clinicians and researchers with a contemporary understanding of the biomarker landscape in CRC. Finally, the review examines future directions and challenges in translating promising biomarkers into clinical practice, with the goal of enhancing personalized medicine approaches for colorectal cancer patients.

Experimental prognostic model integrating N6-methyladenosine-related programmed cell death genes in colorectal cancer

Colorectal cancer (CRC) intricacies, involving dysregulated cellular processes and programmed cell death (PCD), are explored in the context of N6-methyladenosine (m6A) RNA modification. Utilizing the TCGA-COADREAD/CRC cohort, 854 m6A-related PCD genes are identified, forming the basis for a robust 10-gene risk model (CDRS) established through LASSO Cox regression. qPCR experiments using CRC cell lines and fresh tissues was performed for validation. The CDRS served as an independent risk factor for CRC and showed significant associations with clinical features, molecular subtypes, and overall survival in multiple datasets. Moreover, CDRS surpasses other predictors, unveiling distinct genomic profiles, pathway activations, and associations with the tumor microenvironment. Notably, CDRS exhibits predictive potential for drug sensitivity, presenting a novel paradigm for CRC risk stratification and personalized treatment avenues.

METTL3 attenuates ferroptosis sensitivity in lung cancer via modulating TFRC

Overexpression of methyltransferase-like 3 (METTL3) is significantly correlated with the malignancy of lung cancer (LC). In the present study, we demonstrated that METTL3 had higher levels in LC tissues relative to normal tissues. METTL3 showed superior sensitivity and specificity for diagnosis and identification of LC functions. In addition, silencing METTL3 resulted in enhanced ferroptosis sensitivity, whereas overexpression of METTL3 exhibited the opposite effect. Inhibition of METTL3 impeded LC growth in cell-derived xenografts. Further exploratory studies found that METTL3 stimulated the low expression of transferrin receptor (TFRC), which was critical for ferroptosis sensitization in LC cells induced by silenced METTL3, as silencing of TFRC caused a decrease in negative regulators of ferroptosis (FTH1 and FTL) in METTL3 knockdown A549 and PC9 cells. Finally, we confirmed that METTL3 attenuation effectively maintained the stability of TFRC mRNA. In conclusion, we reported a novel mechanism of METTL3 desensitization to ferroptosis via regulating TFRC, and an appropriate reduction of METTL3 might sensitize cancer cells to ferroptosis-based therapy.

CircRNA circSTIL inhibits ferroptosis in colorectal cancer via miR-431/SLC7A11 axis

Ferroptosis is an emerging programmed cell death and plays essential roles in tumorigenesis, including colorectal cancer (CRC). The present study intended to disclose the role of a novel oncogene circular RNA (circRNA) circSTIL in CRC phenotypes, especially ferroptosis. The expression of circSTIL was measured in CRC tissues and cells. Then, the impacts of circSTIL expression on the proliferation and ferroptosis of CRC cells were examined by loss-of-function assays in vitro. Bioinformatics, luciferase reporter assay and cell rescue assay were further performed to reveal the ceRNA-associated mechanism of circSTIL. CircSTIL was significantly upregulated in CRC. Cell proliferation was suppressed while ferroptosis was induced with the silencing of circSTIL in CRC cells. Interestingly, circSTIL competed with miR-431 for solute carrier family 7 member 11 (SLC7A11) binding. Additionally, miR-431 suppression or SLC7A11 overexpression overturned circSTIL silencing-mediated cell phenotypes in CRC cells. CircSTIL promotes CRC cell proliferation and suppresses ferroptosis in vitro via miR-431/SLC7A11 signaling, revealing the pathogenesis of CRC, and providing potential therapeutic targets of CRC.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

Ferroptosis: Reviewing CRC with the Third Eye

Colorectal cancer (CRC) has been one of the most common cancers and maintains the second-highest incidence and mortality rates among all cancers. The high risk of recurrence and metastasis and poor survival are still huge challenges in CRC therapy, in which the discovery of ferroptosis provides a novel perspective. It has been ten years since a unique type of regulated cell death driven by iron accumulation and lipid peroxidation was proposed and named ferroptosis. During the past decade, there have been multiple pieces of evidence suggesting that ferroptosis participates in the pathophysiological processes during disease progression. In this review, we describe ferroptosis as an imbalance of oxidant systems and anti-oxidants which results in lipid peroxidation, membrane damage, and finally cell death. We elaborate on the mechanisms of ferroptosis and systematically summarize recent studies on the regulatory pathways of ferroptosis in CRC from various perspectives, ranging from encoding genes, noncoding RNAs to regulatory proteins. Finally, we discuss the potential therapeutic role of ferroptosis in CRC treatments.

Novel characterization discoveries of ferroptosis-associated molecules in COAD microenvironment based TCGA data

Background and Objective: One of the most recent forms of programmed cell death, ferroptosis, is crucial in tumorigenesis. Ferroptosis is characterized by iron-dependent oxidative destruction of cellular membranes following the antioxidant system's failure. However, it is unknown whether ferroptosis-related genes (FRGs) are associated with colon adenocarcinoma (COAD) metastasis, immune cell infiltration, and oxidative stress in COAD. The current study concentrated on FRGs expression in colon cancer metastasis, their relationship to immune cell infiltration (ICI), and potential pathological pathways in COAD. Methods and Results: Clinical information and mRNA expression patterns for patients with COAD metastasis were obtained from the public TCGA database. Patients with low mRNA levels showed good overall survival than patients with high mRNA levels. The genomic-clinicopathologic nomogram was subsequently created by combining risk score and clinicopathological features. Absolute Shrinkage and Selection Operator have shown a 4 gene signature that can stratify cancer patients into high-risk versus low-risk. These four FRGs were found to be significantly linked to the overall survival of COAD patients and predicted high risk score. Next, age, stage, and PTNM were combined in univariate and multivariate cox regression models to perform a filtering procedure. The receiver operating characteristic (ROC) and calibration curves indicated that constructed signature model exhibited high prediction accuracy and clinical relevance in COAD. ARID3A showed a strong negative correlation with a wide range of immune tumour-infiltrating cells in COAD microenvironment. According to the single sample gene set enrichment analysis (ssGSEA) results, FRGs are involved in variety of pathological pathways including PI3K-AKT-mTOR pathway, reactive oxygen species (ROS) pathway, response to hypoxia pathway, and other inflammation related pathways. Moreover, dysregulation of FRGs in COAD patients showed a significance correlation with wide range of miRNAs and transcription factors (TFs). Conclusion: We identified new diagnostic biomarkers and established prognostic models for ferroptosis related programmed cell death in COAD metastasis. FRGs may improve tumor cell survival by activating the TGFB pathway, which can stimulate ROS production, accelerates ECM breakdown, and promote tumor progression and invasion. Genes implicated in ferroptosis, as revealed by the Kaplan Meier and a genomic-clinicopathologic nomogram, are potential therapeutic targets and prognosis indications for metastasis COAD patients.

Ferroptosis-based nano delivery systems targeted therapy for colorectal cancer: Insights and future perspectives

There are limited options for patients who develop liver metastasis from colorectal cancer (CRC), the leading cause of cancer-related mortality worldwide. Emerging evidence has provided insights into iron deficiency and excess in CRC. Ferroptosis is an iron-dependent form of programmed cell death characterized by aberrant iron and lipid metabolism, which play crucial roles in tumorigenesis, tumor progression, and treatment options. A better understanding of the underlying molecular mechanism of ferroptosis has shed light on the current findings of ferroptosis-based nanodrug targeting strategies, such as driving ferroptosis in tumor cells and the tumor microenvironment, emerging combination therapy and against multidrug resistance. Furthermore, this review highlights the challenge and perspective of a ferroptosis-driven nanodrug delivery system for CRC-targeted therapy.

The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer

BACKGROUND

Findings from numerous studies have revealed that ferroptosis is closely related to tumorigenesis and immune cell infiltration. Long non-coding RNAs (lncRNAs) are reportedly involved in the progression of various cancers, including prostate cancer (PCa). This study was designed to establish a ferroptosis-related lncRNA (frlncRNA) signature to predict PCa prognosis.

METHODS

The frlncRNAs were identified by studying their expression by Pearson's correlation analysis. Differentially expressed prognosis related frlncRNAs were identified by the Wilcoxon test and univariate Cox regression analysis. The LASSO Cox regression model was used to build a model to predict biochemical recurrence (BCR) based on frlncRNAs. The GSEA software (version 4.1.0) was used to explore the enriched pathways in high- and low- risk groups. Patients with PCa were clustered into different subgroups by unsupervised clustering based on the frlncRNAs considered in the prognostic model. Real-time PCR and CCK8 assays were performed to verify the expression and function of frlncRNAs.

RESULTS

We identified 35 differentially expressed prognosis related frlncRNAs based on data on PCa from TCGA. A risk signature based on five frlncRNAs (AP006284.1, AC132938.1, BCRP3, AL360181.4 and AL135999.1), was confirmed to perform well in predicting BCR. The high-risk group had higher disease grades and a greater number of infiltrating immune cells. Besides this, we found that the five frlncRNAs were connected with typical immune checkpoints. With respect to molecular mechanisms, several metabolic pathways were found to enriched in the low-risk group. Furthermore, patients could be classified into different subtypes with different PSA-free times using the five frlncRNAs. Notably, AP006284.1, AC132938.1, BCRP3 and AL135999.1 were upregulated in PCa cells and tissues, whereas AL360181.4 exhibited the opposite trend. The downregulation of BCRP3 and AP006284.1 impaired the proliferation of 22RV1 cells.

CONCLUSION

We generated a prognostic model based on five frlncRNAs, with clinical usefulness, and thus provided a novel strategy for predicting the BCR of patients with PCa.

Prognostic and Predictive Models for Left- and Right- Colorectal Cancer Patients: A Bioinformatics Analysis Based on Ferroptosis-Related Genes

Background

Left- and right-sided colorectal cancer (LCRC, RCRC) are significantly different in epidemiology and clinical manifestations and have altered outcomes. However, as a hot tumor prognostic marker, the role of ferroptosis-related genes (FRGs) in LCRC and RCRC is unknown.

Methods

From The Cancer Genome Atlas (TCGA) database, we downloaded the expression profiles of CRC patients. A "DESeq2" package was performed to compare the differentially expressed genes (DEGs) of LCRC and RCRC. FRGs were identified using the FerrDb. The prognostic value of differentially expressed FRG (DE-FRG) in left- and right-CRC was assessed separately by Cox regression analysis. Subsequently, functional enrichment analysis, ESTIMATE, and single sample Gene Set Enrichment Analysis (ssGSEA) were performed based on LCRC and RCRC samples to reveal the potential function of FRGs-related risk signatures. The differential expression of FRGs in tumor tissues and adjacent normal tissues were verified by Western blot. The differential expression and prognosis in LCC and RCC were verified by immunohistochemistry.

Results

Based on the identified 14 DE-FRGs, the LCRC prognostic model consisted of NOS2 and IFNG; NOS2 and ALOXE established the prognostic signature that could distinguish RCRC outcomes. In the functional analysis, the DEGs (high risk vs. low risk) of the LCRC and RCRC were significantly enriched in the immune- and lipid-related terms and pathways. ESTIMATE and ssGSEA suggested that these FRGs-related risk signatures were affiliated with the infiltration of immune cell subtypes. Western blotting results showed that NOS2 and ALOXE3 were significantly highly expressed in cancer, and the difference was statistically significant (P < 0.05). Immunohistochemical results showed that ALOXE3 was highly expressed in RCC, and those with high expression had a worse prognosis, while NOS2 gene had an effect on the prognosis of both LCC and RCC.

Conclusion

This study constructed a potential prognostic model of LCRC and RCRC, respectively. We also identified the crucial pathways that contribute to elucidating the pathogenesis of CRC.

Comprehensive Analysis of Immune Infiltrates of Ferroptosis-Related Long Noncoding RNA and Prediction of Colon Cancer Patient Prognoses

Ferroptosis is a newly defined mode of programmed oxidative cell death. Knowledge of ferroptosis-related long noncoding (lnc) RNA in the tumor immune microenvironment of colon cancer is lacking. We systematically analyzed the correlations between ferroptosis-related lncRNAs and the tumor microenvironment, immune cell infiltration, and patient prognosis for 379 colon cancer samples in the Cancer Genome Atlas (TCGA). Using consensus clustering, we divided the 379 colon cancer patients into two subgroups (clusters 1 and 2) based on the differentially expressed ferroptosis-related lncRNAs. Cluster 1 was preferentially associated with longer overall survival, upregulated immune checkpoint inhibitor expressions, higher immunoscores, higher stromal scores, higher estimated scores, and distinct immune cell infiltration. Cancer- and metabolism-related pathways were enriched by gene set enrichment analyses. We constructed a prognostic signature of 15 ferroptosis-related lncRNAs (ZEB1-AS1, LINC01011, AC005261.3, LINC01063, LINC02381, ELFN1-AS1, AC009283.1, LINC02361, AC105219.1, AC002310.1, AL590483.1, MIR4435-2HG, NKILA, AC021054.1, and AL450326.1) and divided the patients into the high- and low-risk-score groups. The signature was validated using TCGA training and testing cohorts. The risk signature was an independent prognostic factor for predicting survival and excellently predicted the prognoses of patients with colon cancer. Moreover, the risk signature was related to immune characteristics. Chemosensitivity analyses showed that low-risk-score patients were more sensitive to sorafenib. In summary, our work revealed the important role of ferroptosis-related lncRNAs in the tumor microenvironment and immune cell infiltration and may help determine personalized prognoses and treatment for patients with colon cancer.

Construction and validation of a risk scoring model for diffuse large B-cell lymphoma based on ferroptosis-related genes and its association with immune infiltration

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Categorization of DLBCL into four clusters based on survival- and ferroptosis-related factors.

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Establishment of an efficient risk scoring model is established for patients with DLBCL.

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Ferroptosis-based risk scoring model reveals immune infiltration correlation in DLBCL.

Backgrounds

The prognostic significance of ferroptosis-related genes is well known. However, survival- and ferroptosis-related genes are not currently considered in risk scoring models for diffuse large B-cell lymphoma (DLBCL).

Materials and methods

Ferroptosis regulators and markers were downloaded from the FerrDb database. The transcriptome profiling data were collected from the cancer genome atlas (TCGA). Transcriptome data and corresponding clinical information of DLBCL were downloaded from the gene expression omnibus (GEO). The validation data were downloaded using the UCSC Xena browser. ConsensusClusterPlus was used to categorize DLBCL samples according to gene expression profiles. The survival function was plotted with the Kaplan-Meier plots. The nomogram was built using multivariate logistic regression analysis and the Cox proportional hazards regression model.

Results

Based on the GSE11318 dataset of 203 samples and 267 ferroptosis-related gene expression profiles, we identified four clusters. A total of 19 survival-related genes were found associated with ferroptosis. The prognostic risk scoring model was constructed based on the regression coefficients. The obtained area under the receiver operating characteristic curve (AUC) values were 0.769, 0.801, and 0.791 for 1-, 3-, and 5-year survival, respectively. DLBCL samples with cluster 2 or cancer stage IV have shorter survival. Correlations between the immune infiltration and risk scores of the 12 immune cells were demonstrated. The response of DLBCL to doxorubicin was effectively validated by the risk scoring model.

Conclusions

In this study, a ferroptosis-based risk scoring model for patients with DLBCL was constructed and validated in an independent dataset. This risk score model has a better efficacy in predicting survival compared to clinical characteristics.

A New Ferroptosis-Related lncRNA Signature Predicts the Prognosis of Bladder Cancer Patients

Background: Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients.

Methods: We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed.

Results: We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel.

Conclusion: The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.

Identification of the Prognostic Signature Associated With Tumor Immune Microenvironment of Uterine Corpus Endometrial Carcinoma Based on Ferroptosis-Related Genes

Background: Uterine corpus endometrial carcinoma (UCEC) is the sixth most common cancer worldwide. Ferroptosis plays an important role in malignant tumors. However, the study of ferroptosis in the endometrial carcinoma remains blank.

Methods: First, we constructed a ferroptosis-related signature based on the expression profiles from The Cancer Genome Atlas database. Then, patients were divided into the high-risk and low-risk groups based on this signature. The signature was evaluated by Kaplan–Meier analysis and receiver operating characteristic (ROC) analysis. We further investigated the relationship between this signature and immune microenvironment via CIBERSORT algorithm, ImmuCellAI, MAF, MSI sensor algorithm, GSEA, and GDSC.

Results: This signature could be an independent prognostic factor based on multivariate Cox regression analysis. GSEA revealed that this signature was associated with immune-related phenotype. In addition, we indicated the different status of immune infiltration and response to the immune checkpoint between low-risk and high-risk groups. Patients in the low-risk group were more likely to present with a higher expression of immune checkpoint molecules and tumor mutation burden. Meanwhile, the low-risk patients showed sensitive responses to chemotherapy drugs.

Conclusion: In summary, the six ferroptosis-related genes signature could be used in molecular subgrouping and accurately predict the prognosis of UCEC.

Prognostic implications of ferroptosis-associated gene signature in colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) is one of the most common and fatal malignant tumors, which increases the difficulty of prognostic predictions. Thus, new biomarkers for the diagnosis and prognosis of COAD should be explored. Ferroptosis is a recently identified programmed cell death process that has the characteristics of iron-dependent lipid peroxide accumulation. However, the predictive value of ferroptosis-related genes (FRGs) for COAD still needs to be further clarified.

AIM

To identify some critical FRGs and construct a COAD patient prognostic signature for clinical utilization.

METHODS

The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus databases were the data sources for mRNA expression and corresponding COAD patient clinical information. Differentially expressed FRGs were recognized using R and Perl software. We constructed a multi-FRG signature of the TCGA-COAD cohort by performing a univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis. COAD patients from the Gene Expression Omnibus cohort were utilized for verification.

RESULTS

Our research showed that most of the FRGs (85%) were differentially expressed between the corresponding adjacent normal tissues and cancer tissues in the TCGA-COAD cohort. Seven FRGs were related to overall survival (OS) in the univariate Cox analysis (all P < 0.05). A model with five FRGs (AKR1C1, AKR1C3, ALOX12, CRYAB, and FDFT1) was constructed to divide patients into high- and low-risk groups. The OS of patients in the high-risk group was significantly lower than that of the low-risk group (all P < 0.01 in the TCGA and Gene Expression Omnibus cohorts). The risk score was an independent prognosticator of OS in the multivariate Cox analysis (hazard ratio > 1, P < 0.01). The predictive capacity of the model was verified by a receiver operating characteristic curve analysis. In addition, a nomogram based on the expression of five hub FRGs and risk score can precisely predict the OS of individual COAD cancer patients. Immune correlation analysis and functional enrichment analysis results revealed that immunology-related pathways were abundant, and the immune states of the high-risk group and the low-risk group were different.

CONCLUSION

In conclusion, a novel five FRG model can be utilized for predicting prognosis in COAD. Targeting ferroptosis may be a treatment option for COAD.

Identification of a Novel Ferroptosis-Related Gene Prognostic Signature in Bladder Cancer

Background

Ferroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined.

Methods

FRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.

Results

Thirty-two significantly different FRGs were identified from TCGA–BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan–Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.

Conclusion

Herein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.

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.

Molecular subtypes based on ferroptosis-related genes and tumor microenvironment infiltration characterization in lung adenocarcinoma

Recently, several molecular subtypes with different prognosis have been found in lung adenocarcinoma (LUAD). However, the characteristics of the ferroptosis molecular subtypes and the associated tumor microenvironment (TME) cell infiltration have not been fully studied in LUAD. Using 1160 lung adenocarcinoma samples, we explored the molecular subtypes mediated by ferroptosis-related genes, along with the associated TME cell infiltration. The ferroptosis score was constructed using the least absolute shrinkage and selection operator regression (LASSO) method to quantify the ferroptosis characteristics of a single tumor. Three different molecular subtypes related to ferroptosis, with different prognoses, were identified in LUAD. Analysis of TME cell infiltration revealed immune heterogeneity among the three subtypes. Cluster A was characterized by immunosuppression and was associated with stromal activation. Cluster C was characterized by a large number of immune cells infiltrating the TME, promoting tumor immune response, and it was significantly enriched in immune activation-related signaling pathways. Relatively less infiltration of immune cells was a feature of cluster B. The ferroptosis score can predict tumor subtype, immunity and prognosis. A low ferroptosis score was characterized by immune activation and good prognosis, as seen in the cluster C subtype. Relative immunosuppression and poor prognosis were the characteristics of a high ferroptosis score, as seen in cluster A and B subtypes. At the same time, the anti-PD-1/L1 immunotherapy cohort demonstrated that a low ferroptosis score was associated with higher efficacy of immunotherapy. The ferroptosis score is a promising biomarker that could be of great significance to determine the prognosis, molecular subtypes, TME cell infiltration characteristics and immunotherapy effects in patients with LUAD.

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.