Long Non-coding RNA LINC02474 Affects Metastasis and Apoptosis of Colorectal Cancer by Inhibiting the Expression of GZMB

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer

PURPOSE

This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis.

METHODS

SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses.

RESULTS

Our analysis revealed that 48 DEPCDGs are significantly correlated with apoptotic signaling and oxidative stress pathways and identified seven key DEPCDGs (CASP3, GADD45B, GNA15, GZMB, IL1B, ISG20, and RHOB) through survival analysis. Furthermore, eight distinct cell subtypes were characterized using scRNA-seq. It was found that G protein subunit alpha 15 (GNA15) exhibited low expression across these subtypes and a strong association with immune cells. Based on the DEGs identified by the GNA15 high- and low-expression groups, a prognostic model comprising eight genes with significant prognostic value was constructed, effectively predicting patient overall survival. Additionally, a nomogram incorporating the RS signature, age, grade, and stage was developed and validated using two large SOC datasets.

CONCLUSION

GNA15 emerged as an independent and excellent prognostic marker for SOC patients. This study provides valuable insights into the prognostic potential of DEPCDGs in SOC, presenting new avenues for personalized treatment strategies.

Coding and noncoding RNA profile of human heterotopic ossifications - Risk factors and biomarkers

Heterotopic ossification (HO) means the formation of bone in muscles and soft tissues, such as ligaments or tendons. HO could have a genetic history or develop after a traumatic event, as a result of muscle injury, fractures, burns, surgery, or neurological disorders. Many lines of evidence suggest that the formation of HO is related to the pathological differentiation of stem or progenitor cells present within soft tissues or mobilized from the bone marrow. The cells responsible for the initiation and progression of HO are generally called HO precursor cells. The exact mechanisms behind the development of HO are not fully understood. However, several factors have been identified as potential contributors. For example, local tissue injury and inflammation disturb soft tissue homeostasis. Inflammatory cells release growth factors and cytokines that promote osteogenic or chondrogenic differentiation of HO precursor cells. The bone morphogenetic protein (BMP) is one of the main factors involved in the development of HO. In this study, next-generation sequencing (NGS) and RT-qPCR were performed to analyze the differences in mRNA, miRNA, and lncRNA expression profiles between muscles, control bone samples, and HO samples coming from patients who underwent total hip replacement (THR). As a result, crucial changes in the level of gene expression between HO and healthy tissues were identified. The bioinformatic analysis allowed to describe the processes most severely impacted, as well as genes which level differed the most significantly between HO and control samples. Our analysis showed that the level of transcripts involved in leukocyte migration, differentiation, and activation, as well as markers of chronic inflammatory diseases, that is, miR-148, increased in HO, as compared to muscle. Furthermore, the levels of miR-195 and miR-143, which are involved in angiogenesis, were up-regulated in HO, as compared to bone. Thus, we suggested that inflammation and angiogenesis play an important role in HO formation. Importantly, we noticed that HO is characterized by a higher level of TLR3 expression, compared to muscle and bone. Thus, we suggest that infection may also be a risk factor in HO development. Furthermore, an increased level of transcripts coding proteins involved in osteogenesis and signaling pathways, such as ALPL, SP7, BGLAP, BMP8A, BMP8B, SMPD3 was noticed in HO, as compared to muscles. Interestingly, miR-99b, miR-146, miR-204, and LINC00320 were up-regulated in HO, comparing to muscles and bone. Therefore, we suggested that these molecules could be important biomarkers of HO formation and a potential target for therapies.

Identification of apoptosis-related key genes and the associated regulation mechanism in thoracic aortic aneurysm

BACKGROUND

This study investigated the role of apoptosis-related genes in thoracic aortic aneurysms (TAA) and provided more insights into TAA's pathogenesis and molecular mechanisms.

MATERIAL/METHODS

Two gene expression datasets (GSE9106 and GSE26155) were retrieved from the Gene Expression Omnibus (GEO) database. Apoptosis-related genes were obtained from the KEGG apoptosis pathway (hsa04210). Differentially expressed apoptosis-related genes were identified by performing differential expression analysis using limma for TAA blood and tissue samples. GO and KEGG enrichment analysis of the differentially expressed apoptosis genes was performed using the Metascape web tool. The miRNA-mRNA regulatory network was reconstructed using the ENCORI and miRDB databases, and functional enrichment analysis was performed on the related miRNAs using the miEAA tool. The correlation between the expression levels of differentially expressed apoptosis-related genes and genes involved in immune infiltration in TAA was calculated using the CIBERSORT algorithm. The apoptosis modification patterns mediated by differentially expressed apoptosis-related genes were systematically assessed in TAA samples.

RESULTS

A total of 9 differentially-expressed apoptosis-related genes were identified in TAA samples compared with normal samples. 150 miRNAs and 6 mRNAs regulatory networks were reconstructed using the ENCORI and miRDB databases. Immune infiltration analysis revealed that the GZMB had the strongest positive correlation with activated NK cells and the DFFA presented the strongest positive correlation with T cells follicular helper. 3 distinct apoptosis modification patterns mediated by 9 differentially-expressed apoptosis-related genes were identified. They differ in immune characteristics and drug sensitivity, and their biological functions in these subtypes were further studied.

CONCLUSIONS

This study identified key apoptosis-related genes related to TAA and evaluated the modification patterns of key apoptosis genes in TAA, providing insights into potential targets and mechanisms of TAA pathogenesis and progression.

The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation

Background: Necroptosis contributes significantly to colon adenocarcinoma (COAD). We aim to assess the relationship between immunoinfiltration and stemness in COAD patients through the development of a risk score profile using necroptosis-related long noncoding RNAs (NRLs). Methods: Our study was based on gene expression data and relevant clinical information from The Cancer Genome Atlas (TCGA). Necroptosis-related genes (NRGs) were obtained from the Kyoto Encyclopedia of Genes and Genome (KEGG) database. Pearson correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression were used to determine the NRL prognositic signature (NRLPS). NRLs expression was examined using qRT-PCR method. Several algorithms were used to identify relationships between immune cell infiltration and NRLPS risk scores. Further analysis of somatic mutations, tumor stemness index (TSI), and drug sensitivity were also explored. Results: To construct NRLPS, 15 lncRNAs were investigated. Furthermore, NRLPS patients with high-risk subgroups had lower survival rates than that of patients with low-risk subgroups. Using GSEA analysis, NRL was found to be enriched in Notch, Hedgehog and Smoothened pathways. Immune infiltration analysis showed significant differences in CD8+ T cells, dendritic cell DCs, and CD4+ T cells between the two risk groups. In addition, our NRLPS showed a relevance with the regulation of tumor microenvironment, tumor mutation burden (TMB) and stemness. Finally, NRLPS demonstrated potential applications in predicting the efficacy of immunotherapy and chemotherapy in patients with COAD. Conclusion: Based on NRLs, a prognostic model was developed for COAD patients that allows a personalized tailoring immunotherapy and chemotherapy to be tailored.

CircSTK3 drives the metastasis of colorectal cancer by regulating epithelial-mesenchymal transition

Circular RNAs (circRNAs) play crucial roles in malignancies. We aimed to delineate the functions and clinical importance of dysregulated circRNAs in colorectal cancer (CRC). We determined the circRNA expression profile from five CRC and paired adjacent normal tissues using circRNA microarray. We found that a novel circRNA, hsa_circ_0004592 (named circSTK3), was significantly upregulated in CRC tissues and correlated with decreased survival. Loss- and gain-of-function assays revealed that circSTK3 promoted the migration and invasion but not proliferation of cells. Whole genome expression microarray identified potential downstream targets and the regulatory networks of circSTK3; Gene Ontology analysis confirmed circSTK3 involvement in the CRC metastasis phenotype. Abnormal circSTK3 expression affected a subset of genes associated with CRC metastasis and triggered epithelial-mesenchymal transition programming, maintaining a tumor-promoting signature. Moreover, circSTK3 was transcriptionally regulated by CTCF. These findings reveal the functional and prognostic roles of circSTK3 and expose circRNAs as key players in metastasis.

Metabolism-related lncRNAs signature to predict the prognosis of colon adenocarcinoma

BACKGROUND

Cell metabolism and long noncoding RNA (lncRNA) played crucial roles in cancer development. However, their association in colon adenocarcinoma (COAD) remains unclear.

METHODS

The COAD gene expression data and corresponding clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. Differential expression of metabolic genes and lncRNA were identified by comparing tumor and normal colon tissues. Pearson correlation analysis was performed to identify metabolism-associated lncRNA. COAD patients were divided into training cohort and validation cohort by randomization. Then, a univariate Cox regression analysis was introduced to evaluate the correlations between metabolism-related lncRNAs and overall survival (OS) of the patients in the training cohort. The least absolute shrinkage and selection operator (LASSO) method was introduced to determine and establish a prognostic prediction model. Subsequently, survival analysis, receiver operating characteristic (ROC) curve analysis, and Cox regression analysis were generated to estimate the prognostic role of the LncRNA risk score in training, validation, and entire cohorts.

RESULTS

We identified 152 differentially expressed metabolism-associated lncRNAs (MRLncRNAs). A prognostic prediction model involving four metabolism-related lncRNAs were established using LASSO. In each cohort, COAD patients in the high-risk group had worse OS compared to those in the low-risk group. The ROC analyses demonstrated that the lncRNA signature performed well in predicting OS. Uni- and multivariate analysis indicated that the lncRNA signature as an independent prognostic factor. Furthermore, a correlation analysis demonstrated that LINC01138 was the most closely lncRNA related to metabolic genes. In vitro assays demonstrated that LINC01138 affects tumor progression in COAD.

CONCLUSIONS

In summary, we established a metabolism-associated lncRNAs model to predict the prognosis in COAD patients.

Effective natural inhibitors targeting granzyme B in rheumatoid arthritis by computational study

Background

Rheumatoid arthritis (RA) is an autoimmune disease characterized by erosive arthritis, and current treatments for RA fall short of the outcomes expected by clinicians and patients.

Objectives

This study aimed to identify novel therapeutic and prognostic targets in RA at the genomic level and to screen desirable compounds with potential inhibitory effects on GZMB.

Methods

We performed differential gene analysis on GSE55235 and GSE55457 from Gene Expression Omnibus (GEO) and then obtained the intersection of the two differentially expressed genes (DEGs) lists by drawing Venn diagrams. Then we performed protein-protein interaction (PPI) network analysis, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis on the DEGs of the intersection. Next, we downloaded the crystal structure of Granzyme B (GZMB). Molecular docking technology was used to screen potential inhibitors of GZMB in subsequent experiments, and we then analyzed the toxicity and water solubility of these potential inhibitors for future drug experiments. Finally, whether the docking of these small molecules with GZMB is stable is tested by molecular dynamics.

Results

A total of 352 mutual DEGs were identified. Twenty hub genes were obtained according to PPI network analysis, among which the GZMB gene attracted the attention of our research. Three potent natural compounds, ZINC000004557101, ZINC000012495776, and ZINC000038143593, bound to GZMB, show better binding affinity. Furthermore, they are predicted to own low Ames mutagenicity, developmental toxicity potential, rodent carcinogenicity, and high tolerance to cytochrome P4502D6. Molecular dynamics simulations show that ZINC000004557101 and GZMB have more advantageous potential energy and can exist stably in a natural environment. Moreover, we finally verified the inhibitory effect of ZINC000004557101 on granzyme B by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and Western blotting experiment.

Conclusion

RA patients showed increased GZMB expression. ZINC000004557101 is a potential drug targeting GZMB for treating RA.

Apoptosis evasion via long non-coding RNAs in colorectal cancer

Long non-coding RNA (LncRNA) is a novel and diverse class of regulatory transcripts that are frequently dysregulated in numerous tumor types. LncRNAs are involved in a complicated molecular network, regulating gene expression, and modulating diverse cellular activities in different cancers including colorectal cancer (CRC). Evidence indicates that lncRNAs can be used as a potential biomarker for the prognosis and diagnosis of CRC as they are aberrantly expressed in CRC cells. The high expression or silencing of lncRNAs is associated with cell proliferation, invasion, metastasis, chemoresistance and apoptosis in CRC. LncRNAs exert both pro-apoptotic and anti-apoptotic functions in CRC. The expression of some oncogene lncRNAs is upregulated which leads to the inhibition of apoptotic pathways, similarly, the tumor suppressor lncRNAs are downregulated in CRC. In this review, we describe the function and mechanisms of lncRNAs to regulate the expression of genes that are involved directly or indirectly in controlling cellular apoptosis in CRC. Furthermore, we also discussed the different apoptotic pathways in normal cells and the mechanisms by which CRC evade apoptosis.

Influences of miR-378a-3p on the Pathogenesis of Allergic Rhinitis via GzmB-Mediated Inflammatory Reaction

Methods

Totally, 24 BALB/c mice were assigned to the AR group, control group, GzmB group, and blank group (each n = 6). The blank group was normally fed without treatment, and the other three groups were treated by ovalbumin (OVA) to induce AR models, in which the GzmB group was intranasally injected with lentiviral vector suppressing GzmB expression during the second immunization, while the control group was given the GzmB-blank vector. The times of AR pathological behaviours such as sneezing and scratching the nose of mice were observed and counted. The nasal lavage fluid of each mouse was acquired, and then, the mouse was executed by cervical dislocation, followed by collection of blood and nasal mucosa tissues. Then, ELISA was adopted for quantifying immunoglobulin E (IgE), interleukin (IL)-4, IL-6, and histamine (HA), and nasal mucosa tissues were treated by HE and TUNEL staining to observing their histopathological manifestations. PCR and western blot (WB) were adopted for quantifying GzmB and miR-378a-3p. Additionally, with NP69 cells, dual luciferase reporter (DLR) assay was carried out for determining the targeting association of GzmB with miR-378a-3p. Another 24 mice were assigned to the AR group, GzmB group, miR-378a-3p group, and GzmB+ miR-378a-3p group (each n = 6). The AR and GzmB groups were treated as above. The miR-378a-3p group was intervened by lentiviral vector suppressing miR-378a-3p, while the GzmB+ miR-378a-3p group was given GzmB and lentiviral vector suppressing miR-378a-3p meantime. A rescue assay was conducted through repeating the above tests.

Results

The times of sneezing and rubbing the nose and the levels of IgE, IL-4, IL-6, and HA were similar between the control and AR groups (all P > 0.05), and these items of the two groups were all higher than those of the blank and GzmB groups (all P < 0.05). However, no notable difference was observed in IL-4 and IL-6 levels between the GzmB and blank groups (both P > 0.05), while higher levels of other detection results were found in the former group than in the latter (all P < 0.05). The staining results revealed obvious congestion, oedema, and necrosis structures in the nasal mucosa epithelium of the control and AR groups and also revealed a large number of infiltrating eosinophils and notable increase of apoptotic nasal mucosa epithelial cells. The GzmB group showed notably improved nasal mucosa tissues, and its infiltration and apoptosis of eosinophils were more notable than those of the blank group, but notably weaker than those of the AR and control groups. Additionally, the PCR and WB results revealed similar miR-378a-3p and GzmB levels in nasal mucosa between the control and AR groups (both P > 0.05), and a notable decrease of miR-378a-3p and a notable increase of GzmB in both groups (both P < 0.05). The DLR assay revealed notably suppressed fluorescence activity of GzmB-WT in NP69 cells after transfection of miR-378a-3p mimics (P < 0.05) and notably down regulated GzmB protein after increase of miR-378a-3p (P<0.05). Finally, the rescue assay revealed that downregulating miR-378a-3p aggravated the pathological changes of AR (P < 0.05) and also completely reversed the impacts of inhibiting GzmB on the pathological behaviours of AR mice.

Conclusions

MiR-378a-3p can accelerate the pathological development of AR through targeted inhibition on the release of pro-inflammatory factors such as IgE and HA activated by GzmB, so it is a promising molecular target of AR therapy and offers a novel research direction for the complete cure of AR.

Identification of Autophagy-Related LncRNA to Predict the Prognosis of Colorectal Cancer

Objective: To establish a prediction model based on autophagy-related lncRNAs and investigate the functional enrichment of autophagy-related lncRNAs in colorectal cancer.

Methods: TCGA database was used to extract the transcriptome data and clinical features of colorectal cancer patients. HADb was used to obtain autophagy-related genes. Pearson correlation analysis was performed to identify autophagy-related lncRNAs. The autophagy-related lncRNAs with prognostic values were selected. Based on the selected lncRNAs, the risk score model and nomogram were constructed, respectively. Calibration curve, concordance index, and ROC curve were performed to evaluate the predictive efficacy of the prediction model. GSEA was performed to figure out the functional enrichment of autophagy-related lncRNAs.

Results: A total of 13413 lncRNAs and 938 autophagy-related genes were obtained. A total of 709 autophagy-related genes were identified in colon cancer tissues, and 11 autophagy-related lncRNAs (AL138756.1, LINC01063, CD27-AS1, LINC00957, EIF3J-DT, LINC02474, SNHG16, AC105219.1, AC068580.3, LINC02381, and LINC01011) were finally selected and set as prognosis-related lncRNAs. According to the risk score, patients were divided into the high-risk and low-risk groups, respectively. The survival K–M (Kaplan–Meier) curve showed the low-risk group exhibits better overall survival than the high-risk group. The AUCs under the ROC curves were 0.72, 0.814, and 0.83 at 1, 3, and 5 years, respectively. The C-index (concordance index) of the model was 0.814. The calibration curves at 1, 3, and 5 years showed the predicting values were consistent with the actual values. Functional enrichment analysis showed that autophagy-related lncRNAs were enriched in several pathways.

Conclusions: A total of 11 specific autophagy-related lncRNAs were identified to own prognostic value in colon cancer. The predicting model based on the lncRNAs and clinical features can effectively predict the OS. Furthermore, functional enrichment analysis showed that autophagy-related genes were enriched in various biological pathways.

Ferroptosis-Related lncRNA for the Establishment of Novel Prognostic Signature and Therapeutic Response Prediction to Endometrial Carcinoma

Background

Ferroptosis is a recently described form of intentional cellular damage that is iron-dependent and separate from apoptosis, cellular necrosis, and autophagy. It has been demonstrated to be adequately regulated by long noncoding RNAs (lncRNAs) in various cancers. However, the predictive profile of ferroptosis-related lncRNAs (FRLs) in endometrial carcinoma (EC) is unknown. Herein, FRLs associated with uterine corpus endometrial carcinoma (UCEC) prognosis were screened to predict treatment response in EC.

Methods

Samples of EC and adjacent normal tissues were obtained from The Cancer Genome Atlas (TCGA) dataset repository. Limma and survival packages in R software were used to screen FRLs associated with the prognosis of EC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) chord and circle plots of FRLs were also plotted. Next, FRLs screened by the least absolute shrinkage and selection operator (LASSO) method were applied to construct and validate a multivariate Cox proportional risk regression model. Nomogram plots were created to forecast the outcome of UCEC patients, and gene set enrichment analysis (GSEA), principal component analysis (PCA), and immunoassays were performed on the prognostic models. Finally, limma, ggpubr, pRRophetic, and ggplot2 programs were used for drug sensitivity analysis of the prognostic models.

Results

A signature based on nine FRLs (CFAP58-DT, LINC00443, EMSLR, HYI-AS1, ADIRF-AS1, LINC02474, CDKN2B-AS1, LINC01629, and LINC00942) was constructed. The developed FRL prognostic model effectively discriminated UCEC patients into low-risk and high-risk groups. Immunological checkpoints CD80 and CD40 were strongly expressed in the high-risk group. In addition, the nine FRLs were all more expressed in the high-risk group compared to the low-risk group.

Conclusion

These findings significantly contribute to the understanding of the function of FRLs in UCEC and provide promising therapeutic strategies for UCEC.

The role of EphA7 in different tumors

Ephrin receptor A7 (EphA7) is a member of the Eph receptor family. It is widely involved in signal transduction between cells, regulates cell proliferation and differentiation, and participates in developing neural tubes and brain. In addition, EphA7 also has a dual role of tumor promoter and tumor suppressor. It can participate in cell proliferation, migration and apoptosis through various mechanisms, and affect tumor differentiation, staging and prognosis. EphA7 may be a potential diagnostic marker and tumor treatment target. This article reviews the effects of EphA7 on a variety of tumor biological processes and pathological characteristics, as well as specific effects and regulatory mechanisms.

Expression characteristics of long non-coding RNA in colon adenocarcinoma and its potential value for judging the survival and prognosis of patients: bioinformatics analysis based on The Cancer Genome Atlas database

Background

To investigate the expression characteristics of long non-coding RNA (lncRNA) in colon adenocarcinoma (COAD) and its potential value in predicting the prognosis of patient survival.

Methods

We downloaded COAD-related RNA sequencing (RNA-seq) data and patient survival data from The Cancer Genome Atlas (TCGA). The data were analyzed for lncRNA expression differences, subjected to Cox regression analysis for survival rate, and Kaplan-Meier (KM) survival curves were plotted to analyze the role of the key genes related to prognostic survival by pathway enrichment analysis.

Results

The data of 494 COAD clinical samples from TCGA were analyzed; 204 lncRNAs were differentially expressed, 156 were up-regulated, and 48 were down-regulated. The 10 genes with the most significant expression differences were Linc02418, Blacat1, ELFN1-AS1, CRNDE, AC002384.1, AL353801.1, LINC01645, AC073283.2, AC087379.1, and LINC00484. Cox regression analysis of 204 lncRNA genes showed that 23 lncRNA genes with significant effects on the prognosis and survival rate of COAD patients were obtained when P<0.05 was used as the threshold. With P≤0.001 as the threshold, the KM curves of 4 genes (Linc02257, Linc02474, Ac010789.1, Ac083967.1) were statistically significant (P<0.05). The gene Linc02257 was selected for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and it was revealed that the inheritance of Linc02257-regulated gene expression was closely related to tumor development, such as collagen-containing extracellular matrix, organogenesis, activity of membrane protein receptors, and ion channel activity. The signaling pathways regulated by Linc02257 were also closely related to tumors, such as neuroactive ligand-receptor interaction, the PI3K-AKT signaling pathway, calcium signaling pathway, and protein digestion and absorption.

Conclusions

In COAD, lncRNA is differentially expressed and plays an important role in the disease regulation. It has potential application value in the diagnosis, targeted therapy, and prognosis of COAD patients.

A Pyroptosis-Related Gene Signature Predicts Prognosis and Immune Microenvironment for Breast Cancer Based on Computational Biology Techniques

Breast cancer (BC) is a malignant tumor with high morbidity and mortality, which seriously threatens women's health worldwide. Pyroptosis is closely correlated with immune landscape and the tumorigenesis and development of various cancers. However, studies about pyroptosis and immune microenvironment in BC are limited. Therefore, our study aimed to investigate the potential prognostic value of pyroptosis-related genes (PRGs) and their relationship to immune microenvironment in BC. First, we identified 38 differentially expressed PRGs between BC and normal tissues. Further on, the least absolute shrinkage and selection operator (LASSO) Cox regression and computational biology techniques were applied to construct a four-gene signature based on PRGs and patients in The Cancer Genome Atlas (TCGA) cohort were classified into high- and low-risk groups. Patients in the high-risk group showed significantly lower survival possibilities compared with the low-risk group, which was also verified in an external cohort. Furthermore, the risk model was characterized as an independent factor for predicting the overall survival (OS) of BC patients. What is more important, functional enrichment analyses demonstrated the robust correlation between risk score and immune infiltration, thereby we summarized genetic mutation variation of PRGs, evaluated the relationship between PRGs, different risk group and immune infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint blockers (ICB), which indicated that the low-risk group was enriched in higher TMB, more abundant immune cells, and subsequently had a brighter prognosis. Except for that, the lower expression of PRGs such as GZMB, IL18, IRF1, and GZMA represented better survival, which verified the association between pyroptosis and immune landscape. In conclusion, we performed a comprehensive bioinformatics analysis and established a four-PRG signature consisting of GZMB, IL18, IRF1, and GZMA, which could robustly predict the prognosis of BC patients.

Immune Infiltrates of m5C RNA Methylation-Related LncRNAs in Uterine Corpus Endometrial Carcinoma

Aberrant 5-methylcytidine (m5C) modification plays an essential role in the progression of different cancers. More and more researchers are focusing on developing a lncRNA-based risk model to assess the clinical prognosis of cancer patients. However, the impact of m5C-related lncRNAs on the prognosis of patients with uterine corpus endometrial carcinoma (UCEC), as well as the immune microenvironment of UCEC, remains unclear. Here, we comprehensively analyzed the predictive value of m5C-associated lncRNAs in UCEC and their association with the tumor immune microenvironment, according to the information extracted from the TCGA-UCEC dataset. We identified a total of 32 m5C-associated lncRNAs that were significantly correlated with the prognosis of UCEC patients. Two molecular subtypes were determined by consensus clustering analysis of these 32 m5C-associated prognostic lncRNAs. Further data showed that cluster 1 was associated with poor clinical prognosis, advanced tumor grade, higher PD-L1 expression levels, higher ESTIMATEScore, and higher immuneScore, as well as the immune cell infiltration. Then, 17 m5C-associated lncRNAs with prognostic values were obtained using LASSO regression analysis. And a risk model was constructed based on these 17 lncRNAs. It was revealed that the risk model could be used as an independent factor for UCEC prognosis. In addition, patients with UCEC in the high-risk group had higher tumor grades and immune scores. The risk model based on m5C-related lncRNAs was also closely associated with infiltrating immune cells. In conclusion, our study elucidated the crucial roles of the identified m5C-related lncRNAs in the UCEC patients' prognoses, as well as in the immune microenvironment in UCEC. The results suggest that the components of risk models based on the m5C-related lncRNAs may serve as important mediators of the immune microenvironment in UCEC.