Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

The cuproptosis-related signature predicts the prognosis and immune microenvironments of primary diffuse gliomas: a comprehensive analysis

BACKGROUND

Evidence has revealed a connection between cuproptosis and the inhibition of tumor angiogenesis. While the efficacy of a model based on cuproptosis-related genes (CRGs) in predicting the prognosis of peripheral organ tumors has been demonstrated, the impact of CRGs on the prognosis and the immunological landscape of gliomas remains unexplored.

METHODS

We screened CRGs to construct a novel scoring tool and developed a prognostic model for gliomas within the various cohorts. Afterward, a comprehensive exploration of the relationship between the CRG risk signature and the immunological landscape of gliomas was undertaken from multiple perspectives.

RESULTS

Five genes (NLRP3, ATP7B, SLC31A1, FDX1, and GCSH) were identified to build a CRG scoring system. The nomogram, based on CRG risk and other signatures, demonstrated a superior predictive performance (AUC of 0.89, 0.92, and 0.93 at 1, 2, and 3 years, respectively) in the training cohort. Furthermore, the CRG score was closely associated with various aspects of the immune landscape in gliomas, including immune cell infiltration, tumor mutations, tumor immune dysfunction and exclusion, immune checkpoints, cytotoxic T lymphocyte and immune exhaustion-related markers, as well as cancer signaling pathway biomarkers and cytokines.

CONCLUSION

The CRG risk signature may serve as a robust biomarker for predicting the prognosis and the potential viability of immunotherapy responses. Moreover, the key candidate CRGs might be promising targets to explore the underlying biological background and novel therapeutic interventions in gliomas.

Exploration of Immunogenic Cell Death-Associated Genes for Predicting Prognosis and Immunological Characteristics in Cervical Squamous Cell Carcinoma

Background. The tumor microenvironment (TME) has gradually entered the vision of researchers and is becoming a vital part of the occurrence of cervical squamous cell carcinoma (CSCC). However, understanding the specific composition of TME still confront enormous challenges, particularly immune and stromal components. Methods. In this study, we performed an unsupervised cluster analysis to determine the immunogenic cell death-associated subtype of CSCC patients. The differences in immune status, genomic alteration, and clinical outcomes between each subtype were compared. Subsequently, we screened vital prognostic factors. The HPA database was employed to verify the protein localization and the expression level between cancer and adjacent tissues. Results. CSCC patients were divided into three subtypes according to the expression of immunogenic cell death-associated genes. Cluster C has the highest survival rate because of the lower activation of tumor-related pathways. The immune score and stromal score of patients with Cluster B were the highest, so it may be considered that stromal tissue inhibits the anti-tumor effect of immunocytes. In addition, we constructed a risk score based on immunogenic cell death-associated genes to screen for vital markers. We systematically revealed the genomic alteration of vital markers. Conclusions. We have established a novel immunogenic cell death-associated risk scoring system in CSCC, and the expression of immunogenic cell death-associated genes may be a valuable biomarker for immunotherapy strategies. Our work may contribute to the development of new immunomodulators and develop new precision immunotherapies for CSCC.

Single-Cell Transcriptomics Reveals Longevity Immune Remodeling Features Shared by Centenarians and Their Offspring

Centenarians, who show mild infections and low incidence of tumors, are the optimal model to investigate healthy aging. However, longevity related immune characteristics has not been fully revealed largely due to lack of appropriate controls. In this study, single-cell transcriptomic analysis of peripheral blood mononuclear cells (PBMCs) derived from seven centenarians (CEN), six centenarians' offspring (CO), and nine offspring spouses or neighbors (Control, age-matched to CO) are performed to investigate the shared immune features between CEN and CO. The results indicate that among all 12 T cell clusters, the cytotoxic-phenotype-clusters (CPC) and the naïve-phenotype-clusters (NPC) significantly change between CEN and ontrol. Compared to Control, both CEN and CO are characterized by depleted NPC and increased CPC, which is dominated by CD8+ T cells. Furthermore, CPC from CEN and CO share enhanced signaling pathways and transcriptional factors associated with immune response, and possesse similar T-cell-receptor features, such as high clonal expansion. Interestingly, rather than a significant increase in GZMK+ CD8 cells during aging, centenarians show accumulation of GZMB+ and CMC1+ CD8 T cells. Collectively, this study unveils an immune remodeling pattern reflected by both quantitative increase and functional reinforcement of cytotoxic T cells which are essential for healthy aging.

Identification of CD8+ T cell infiltration-related genes and their prognostic values in cervical cancer

Cervical cancer is a female-specific cancer with relatively high morbidity and mortality. As known to all, immune cell infiltrations in the cancer microenvironment are closely related to the cancer diagnosis and prognosis. Here we revealed that the CD8+ T cell infiltration was significantly upregulated in cervical cancer versus normal cervix uteri samples. Through univariate and multivariate cox analyses, we discovered that the CD8+ T cell infiltration was the only independent beneficial factor for the prognosis of cervical cancer. To explore the genes associated with the CD8+ T cell infiltration in cervical cancer, we performed the WGCNA analysis on the differentially expressed genes (DEGs) of cervical cancer versus normal cervix uteri tissues. As a result, 231 DEGs were found to be associated with CD8+ T cell infiltration in cervical cancer. Subsequently, with the Cytoscape analysis, we identified 105 hub genes out of the 231 DEGs. To further explore the genes that might be responsible for the prognosis of cervical cancer, we performed a univariate cox analysis followed by a LASSO assay on the 105 hub genes and located four genes (IGSF6, TLR10, FCRL3, and IFI30) finally. The four genes could be applied to the prediction of the prognosis of cervical cancer, and relatively higher expression of these four genes predicted a better prognosis. These findings contributed to our understanding of the prognostic values of CD8+ T cell infiltration and its associated genes in cervical cancer and thus might benefit future immune-related therapies.

Definition of immune molecular subtypes with distinct immune microenvironment, recurrence, and PANoptosis features to aid clinical therapeutic decision-making

Objective: Cervical cancer poses a remarkable health burden to females globally. Despite major advances in early detection and treatment modalities, some patients still relapse. The present study proposed a novel immune molecular classification that reflected distinct recurrent risk and therapeutic responses in cervical cancer.

Methods: We retrospectively collected two cervical cancer cohorts: TCGA and GSE44001. Consensus clustering approach was conducted based on expression profiling of recurrence- and immune-related genes. The abundance of immune cells was inferred via five algorithms. Immune functions and signatures were quantified through ssGSEA. Genetic mutations were analyzed by maftools package. Immunotherapeutic response was inferred via tumor mutation burden (TMB), Tumor Immune Dysfunction and Exclusion (TIDE), and Submap methods. Finally, we developed a LASSO model for recurrence prediction.

Results: Cervical cancer samples were categorized into two immune subtypes (IC1, and IC2). IC2 exhibited better disease free survival (DFS), increased immune cell infiltration within the immune microenvironment, higher expression of immune checkpoints, higher activity of immune-relevant pathways (APC co-inhibition and co-stimulation, inflammation-promoting, MHC class I, IFN response, leukocyte and stromal fractions, macrophage regulation, and TCR Shannon), and higher frequencies of genetic mutations. This molecular classification exhibited a remarkable difference with existing immune subtypes, with diverse PANoptosis (pyroptosis, apoptosis and necroptosis) features. Patients in IC2 were more likely to respond to immunotherapy and targeted, and chemotherapeutic agents. The immune subtype-relevant signature was quantified to predict patients’ recurrence risk.

Conclusion: Altogether, we developed an immune molecular classification, which can be utilized in clinical practice to aid decision-making on recurrence management.

Prognostic Value of GIMAP4 and Its Role in Promoting Immune Cell Infiltration into Tumor Microenvironment of Lung Adenocarcinoma

GIMAPs are recognized as an important regulator in the carcinogenesis and development of lung cancer, but the function of GIMAP4 in the tumor microenvironment (TME) of lung cancers is unclear. In this study, we investigated the expression and variation of GIMAP4 in lung adenocarcinoma (LUAD), to explore its association with infiltration of immune cells. The Cancer Genome Atlas (TCGA) data and Gene Expression Omnibus (GEO) data were analyzed. Infiltration of immune cells was identified with TIMER (Tumor Immune Estimation Resource) and TISIDB (an integrated repository portal for tumor-immune system interactions). GIMAP4 expression declined in non-small-cell lung cancer (NSCLC), correlated with a poor overall survival (OS) in LUAD, indicating that GIMAP4 was a promising prognostic biomarker in LUAD. GIMAP4 mutation frequency was 1.76% in TCGA cohort and was relevant to the expression of immune components. TIMER and CIBERSORT analysis further confirmed that high GIMAP4 expression possibly promoted immune cell infiltration into the TME, with low GIMAP4 impairing the efficacy of immunotherapies targeting common immune check point inhibitors (ICI). GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were performed to provide insights into biological processes involved in LUAD. GIMAP4 was expected to be a prognostic biomarker in LUAD and provides potential adjuvant or neoadjuvant therapeutic strategies for targeting ICIs.

Comprehensive analyses identify RIPOR2 as a genomic instability-associated immune prognostic biomarker in cervical cancer

Cervical cancer (CC) is a malignancy that tends to have a poor prognosis when detected at an advanced stage; however, there are few studies on the early detection of CC at the genetic level. The tumor microenvironment (TME) and genomic instability (GI) greatly affect the survival of tumor patients via effects on carcinogenesis, tumor growth, and resistance. It is necessary to identify biomarkers simultaneously correlated with components of the TME and with GI, as these could predict the survival of patients and the efficacy of immunotherapy. In this study, we extracted somatic mutational data and transcriptome information of CC cases from The Cancer Genome Atlas, and the GSE44001 dataset from the Gene Expression Omnibus database was downloaded for external verification. Stromal components differed most between genomic unstable and genomic stable groups. Differentially expressed genes were screened out on the basis of GI and StromalScore, using somatic mutation information and ESTIMATE methods. We obtained the intersection of GI- and StromalScore-related genes and used them to establish a four-gene signature comprising RIPOR2, CCL22, PAMR1, and FBN1 for prognostic prediction. We described immunogenomic characteristics using this risk model, with methods including CIBERSORT, gene set enrichment analysis (GSEA), and single-sample GSEA. We further explored the protective factor RIPOR2, which has a close relationship with ImmuneScore. A series of in vitro experiments, including immunohistochemistry, immunofluorescence, quantitative reverse transcription PCR, transwell assay, CCK8 assay, EdU assay, cell cycle detection, colony formation assay, and Western blotting were performed to validate RIPOR2 as an anti-tumor signature. Combined with integrative bioinformatic analyses, these experiments showed a strong relationship between RIPOR2 with tumor mutation burden, expression of genes related to DNA damage response (especially PARP1), TME-related scores, activation of immune checkpoint activation, and efficacy of immunotherapy. To summarize, RIPOR2 was successfully identified through comprehensive analyses of the TME and GI as a potential biomarker for forecasting the prognosis and immunotherapy response, which could guide clinical strategies for the treatment of CC patients.

The Role of the Key Differentially Mutated Gene FGFR3 in the Immune Microenvironment of Bladder Cancer

The tumor microenvironment (TME) has been a major focus of research in recent years as a crucial factor in the development and progression of bladder cancer. Unfortunately, the precise composition of TME, particularly the immunological and stromal components, remains unknown. In this work, we downloaded the RNA-seq expression profiles and somatic mutation data of 433 bladder cancer cases from The Cancer Genome Atlas (TCGA) and then employed a comprehensive bioinformatics approach to evaluate them. Firstly, the expression profiles were used to predict the scores and then the content of immune and stromal cells via the estimate package in R software. We then identified differentially expressed genes (DEGs) and differentially mutated genes (DMGs) according to the high-stromal score cohort and low-stromal score cohort. Finally, fibroblast growth factor receptor 3 (FGFR3) was the main differentially mutated gene in bladder carcinoma that we discovered after conducting a cross-study on DEGs and DMGs. Follow-up investigation revealed that FGFR3, whose expression correlated inversely with cancer progression stage, appeared to be a protective factor in bladder cancer. The method of Gene Set Enrichment Analysis (GSEA) was employed to, respectively, interpret the expression data of FGFR3 in high and low expression lists. We observed that the genes in the low FGFR3 expression list were strongly enriched in the biological processes associated with transplantation and cell adhesion, suggesting the possible role of FGFR3 in predicting TME metastasis status in bladder cancer. Therefore, this study is aimed at investigating whether FGFR3 is promising as a biomarker of TME remodeling to explain underlying mechanisms involved in tumorigenesis and metastasis, which may help to make decisions on treatments for bladder cancer.

Identification of Novel Tumor Microenvironment Regulating Factor That Facilitates Tumor Immune Infiltration in Cervical Cancer

Cervical cancer is one of the most common gynecologic malignancies and one of the leading causes of cancer-related deaths in women worldwide. There are more than 30 categories of human papillomavirus infections in the genital tract. The recently discovered immune checkpoint suppression is a potential approach to improve clinical outcomes in these patients by altering immune cell function. However, many questions remain unanswered in terms of this method. For example, the proportion of responders is limited and the exact mechanism of action is uncertain. The tumor microenvironment (TME) has long been regarded as having nonnegligible influence on effectiveness of immunotherapy. The programmed cell death protein 1 (PD-1) pathway has received much attention due to its involvement in activating T-cell immune checkpoint responses. Since tumor cells may evade immune detection and become highly resistant to conventional treatments, anti-PD-1/PD-L1 antibodies are preferred as a kind of cancer treatment and many have just been licensed. To provide a theoretical basis for the development of new therapies, investigating the effect of tumor microenvironment on the prognosis of cervical cancer is necessary. In this work, immunological scores obtained from the ESTIMATE algorithm were used to differentiate between patients with high and low immune cell infiltration. We identified 11 immunologically significant differentially expressed genes (DEGs). For example, CXCR3 was found to be an important factor in CD8⁺ T cell recruitment and tumor immunological infiltration in cervical cancer. These results may lead to novel directions of understanding complex interactions between cancer cells and the tumor microenvironment, as well as new treatment options for cervical cancer.

Bioinformatics Analysis Highlights Five Differentially Expressed Genes as Prognostic Biomarkers of Cervical Cancer and Novel Option for Anticancer Treatment

Cervical cancer is one of the most common gynecological malignancies and is related to human papillomavirus (HPV) infection, especially high-risk type HPV16 and HPV18. Aberrantly expressed genes are involved in the development of cervical cancer, which set a genetic basis for patient prognosis. In this study, we identified a set of aberrantly expressed key genes from The Cancer Genome Atlas (TCGA) database, which could be used to accurately predict the survival rate of patients with cervical squamous cell carcinoma (CESC). A total of 3,570 genes that are differentially expressed between normal and cancerous samples were analyzed by the algorithm of weighted gene co-expression network analysis (WGCNA): 1,606 differentially expressed genes (DEGs) were upregulated, while 1,964 DEGs were downregulated. Analysis of these DEGs divided them into 7 modules including 76 hub genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis revealed a significant increase of genes related to cell cycle, DNA replication, p53 signaling pathway, cGMP-PKG signaling pathway, and Fanconi anemia (FA) pathway in CESC. These biological activities are previously reported to associate with cervical cancer or/and HPV infection. Finally, we highlighted 5 key genes (EMEMP2, GIMAP4, DYNC2I2, FGF13-AS1, and GIMAP1) as robust prognostic markers to predict patient’s survival rate (p = 3.706e-05) through univariate and multivariate regression analyses. Thus, our study provides a novel option to set up several biomarkers for cervical cancer prognosis and anticancer drug targets.

Identification and Validation of a GPX4-Related Immune Prognostic Signature for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a commonly occurring histological subtype of lung cancer. Glutathione peroxidase 4 (GPX4) is an important regulatory factor of ferroptosis and is involved in the development of many cancers, but its prognostic significance has not been systematically described in LUAD. In this study, we focused on developing a robust GPX4-related prognostic signature (GPS) for LUAD. Data for the training cohort was extracted from The Cancer Genome Atlas, and that for the validation cohort was sourced from the GSE72094 dataset including 863 LUAD patients. GPX4-related genes were screened out by weighted gene coexpression network analysis and Spearman’s correlation analysis. Then, Cox regression and least absolute shrinkage and selection operator regression analyses were employed to construct a GPS. The ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and GSEA were utilized to evaluate the relationship between GPS and the tumor microenvironment (TME). We constructed and validated a GPS premised on four GPX4-related genes (KIF14, LATS2, PRKCE, and TM6SF1), which could classify LUAD patients into low- and high-score cohorts. The high-risk cohort presented noticeably poorer overall survival (OS) as opposed to the low-risk cohort, meaning that the GPS may be utilized as an independent predictor of the OS of LUAD. The GPS was also adversely correlated with multiple tumor-infiltrating immune cells and immune-related processes and pathways in TME. Furthermore, greater sensitivity to erlotinib and lapatinib were identified in the low-risk cohort based on the GDSC database. Our findings suggest that the GPS can effectively forecast the prognosis of LUAD patients and may possibly regulate the TME of LUAD.

Identification and Validation of HOTAIRM1 as a Novel Biomarker for Oral Squamous Cell Carcinoma

ORAL squamous cell carcinoma (OSCC) is a malignant tumor with the highest incidence among tumors involving the oral cavity maxillofacial region, and is notorious for its high recurrence and metastasis potential. Long non-coding RNAs (lncRNAs), which regulate the genesis and evolution of cancers, are potential prognostic biomarkers. This study identified HOTAIRM1 as a novel significantly upregulated lncRNA in OSCC, which is strongly associated with unfavorable prognosis of OSCC. Systematic bioinformatics analyses demonstrated that HOTAIRM1 was closely related to tumor stage, overall survival, genome instability, the tumor cell stemness, the tumor microenvironment, and immunocyte infiltration. Using biological function prediction methods, including Weighted gene co-expression network analysis (WGCNA), Gene set enrichment analysis (GSEA), and Gene set variation analysis (GSVA), HOTAIRM1 plays a pivotal role in OSCC cell proliferation, and is mainly involved in the regulation of the cell cycle. In vitro, cell loss-functional experiments confirmed that HOTAIRM1 knockdown significantly inhibited the proliferation of OSCC cells, and arrested the cell cycle in G1 phase. At the molecular level, PCNA and CyclinD1 were obviously reduced after HOTAIRM1 knockdown. The expression of p53 and p21 was upregulated while CDK4 and CDK6 expression was decreased by HOTAIRM1 knockdown. In vivo, knocking down HOTAIRM1 significantly inhibited tumor growth, including the tumor size, weight, volume, angiogenesis, and hardness, monitored by ultrasonic imaging and magnetic resonance imaging In summary, our study reports that HOTAIRM1 is closely associated with tumorigenesis of OSCC and promotes cell proliferation by regulating cell cycle. HOTAIRM1 could be a potential prognostic biomarker and a therapeutic target for OSCC.

Identification of hub genes for early detection of bone metastasis in breast cancer

BACKGROUND

Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers.

METHODS

GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC.

CONCLUSIONS

2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment.

Solute carrier family 12 member 8 (SLC12A8) is a potential biomarker and related to tumor immune cell infiltration in bladder cancer

The solute carrier family has been reported to play critical roles in the progression of several cancers; however, the relationship between solute carrier family 12 member 8 (SLC12A8) and bladder cancer (BC) has not been clearly confirmed. This study explores the prognostic value of SLC12A8 for BC and its correlation with immune cell infiltration. We found that the expression of SLC12A8 mRNA was significantly overexpressed in BC tissues compared with noncancerous tissues in multiple public databases, and the result was validated using real-time PCR and immunohistochemistry (IHC). The Kaplan-Meier method and Cox proportional hazards models were used to evaluate the prognostic value of SLC12A8 for BC. The high expression of SLC12A8 led to a shorter overall survival time and was an unfavorable prognostic biomarker for BC. The mechanisms of SLC12A8 promoting tumorigenesis were investigated by Gene Set Enrichment Analysis (GSEA). Moreover, the correlations of SLC12A8 expression with the tumor-infiltrating immune cells (TICs) in BC were explored using TIMER 2.0 and CIBERSORT. SLC12A8 was associated with CD4+ T cells, dendritic cells, neutrophils, and macrophages infiltration. The expression of SLC12A8 was positively correlated with crucial immune checkpoint molecules. In conclusion, SLC12A8 might be an unfavorable prognostic biomarker in BC related to tumor immune cell infiltration.

Multi-Omics Data Analyses Construct a Six Immune-Related Genes Prognostic Model for Cervical Cancer in Tumor Microenvironment

The cross-talk between tumor cells and the tumor microenvironment (TME) is an important factor in determining the tumorigenesis and progression of cervical cancer (CC). However, clarifying the potential mechanisms which trigger the above biological processes remains a challenge. The present study focused on immune-relevant differences at the transcriptome and somatic mutation levels through an integrative multi-omics analysis based on The Cancer Genome Atlas database. The objective of the study was to recognize the specific immune-related prognostic factors predicting the survival and response to immunotherapy of patients with CC. Firstly, eight hub immune-related prognostic genes were ultimately identified through construction of a protein–protein interaction network and Cox regression analysis. Secondly, 32 differentially mutated genes were simultaneously identified based on the different levels of immune infiltration. As a result, an immune gene-related prognostic model (IGRPM), including six factors (chemokine receptor 7 [CCR7], CD3d molecule [CD3D], CD3e molecule [CD3E], and integrin subunit beta 2 [ITGB2], family with sequence similarity 133 member A [FAM133A], and tumor protein p53 [TP53]), was finally constructed to forecast clinical outcomes of CC. Its predictive capability was further assessed and validated using the Gene Expression Omnibus validation set. In conclusion, IGRPM may be a promising prognostic signature to predict the prognoses and responses to immunotherapy of patients with CC. Moreover, the multi-omics study showed that IGRPM could be a novel therapeutic target for CC, which is a promising biomarker for indicating the immune-dominant status of the TME and revealing the potential mechanisms responsible for the tumorigenesis and progression of CC.