Identification of Immune Cell Infiltration Landscape and Their Prognostic Significance in Uveal Melanoma

Identification and validation of a costimulatory molecule-related signature to predict the prognosis for uveal melanoma patients

Uveal melanoma (UVM) is the most common primary tumor in adult human eyes. Costimulatory molecules (CMs) are important in maintaining T cell biological functions and regulating immune responses. To investigate the role of CMs in UVM and exploit prognostic signature by bioinformatics analysis. This study aimed to identify and validate a CMs associated signature and investigate its role in the progression and prognosis of UVM. The expression profile data of training cohort and validation cohort were downloaded from The Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) dataset. 60 CM genes were identified, and 34 genes were associated with prognosis by univariate Cox regression. A prognostic signature was established with six CM genes. Further, high- and low-risk groups were divided by the median, and Kaplan-Meier (K-M) curves indicated that high-risk patients presented a poorer prognosis. We analyzed the correlation of gender, age, stage, and risk score on prognosis by univariate and multivariate regression analysis. We found that risk score was the only risk factor for prognosis. Through the integration of the tumor immune microenvironment (TIME), it was found that the high-risk group presented more immune cell infiltration and expression of immune checkpoints and obtained higher immune scores. Enrichment analysis of the biological functions of the two groups revealed that the differential parts were mainly related to cell-cell adhesion, regulation of T-cell activation, and cytokine-cytokine receptor interaction. No differences in tumor mutation burden (TMB) were found between the two groups. GNA11 and BAP1 have higher mutation frequencies in high-risk patients. Finally, based on the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) dataset, drug sensitivity analysis found that high-risk patients may be potential beneficiaries of the treatment of crizotinib or temozolomide. Taken together, our CM-related prognostic signature is a reliable biomarker that may provide ideas for future treatments for the disease.

Construction and validation of a novel angiogenesis pattern to predict prognosis and immunotherapy efficacy in colorectal cancer

BACKGROUND

Evidence suggests that the tumor microenvironment (TME) affects the tumor active response to immunotherapy. Tumor angiogenesis is closely related to the TME. Nonetheless, the effects of angiogenesis on the TME of colorectal cancer (CRC) remain unknown.

METHODS

We comprehensively assessed the angiogenesis patterns in CRC based on 36 angiogenesis-related genes (ARGs). Subsequently, we evaluated the prognostic values and therapeutic sensitivities of angiogenesis patterns using multiple methods. We then performed the machine learning algorithm and functional experiments to identify the prognostic key ARGs. Ultimately, the regulation of gut microbiota on the expression of ARGs was further investigated by using whole genome sequencing.

RESULTS

Two angiogenesis clusters were identified and angiogenesis cluster B was characterized by increased stromal and immunity activation with unfavorable odds of survival. Further, an ARG_score including 9 ARGs to predict recurrence-free survival (RFS) was established and its predominant predictive ability was confirmed. The low ARG_score patients were characterized by a high mutation burden, high microsatellite instability, and immune activation with better prognosis. Moreover, patients with high KLK10 expression were associated with a hot tumor immune microenvironment, poorer immune checkpoint blocking treatment, and shorter survival. The in vitro experiments also indicated that Fusobacterium nucleatum (F.n) infection significantly induced KLK10 expression in CRC.

CONCLUSIONS

The quantification of angiogenesis patterns could contribute to predict TME characteristics, prognosis, and individualized immunotherapy strategies. Furthermore, our findings suggest that F.n may influence CRC progression through ARGs, which could serve as a clinical biomarker and therapeutic target for F.n-infected CRC patients.

FOXD1 expression-based prognostic model for uveal melanoma

FOXD1, a new member of the FOX transcription factor family, serves as a mediator and biomarker for cell reprogramming. But its contribution to prognosis of uveal melanoma (UVM) is unclear. This study demonstrated that FOXD1 might promote tumor growth and invasion, because FOXD1 expression was negatively correlated with overall survival, progression-free survival, and disease-specific survival in UVM patients. This conjecture was verified in cell culture with human uveal melanoma cell line (MUM2B) as model cells. Additionally, the biological mechanisms of FOXD1 based on FOXD1-related genomic spectrum, molecular pathways, tumor microenvironment, and drug treatment sensitivity were examined using The Cancer Genome Atlas (TCGA) database, aiming to reasonably explain why FOXD1 leads to poor prognosis of UVM. On these bases, a novel tumor prognostic model was established using the FOXD1-related immunomodulators TMEM173, TNFRSF4, TNFSF13, and ULBP1, which will enable the stratification of disease seriousness and clinical treatment for patients.

Interaction, immune infiltration characteristics and prognostic modeling of efferocytosis-related subtypes in glioblastoma

BACKGROUND

Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation.

METHODS

In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system.

RESULTS

Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy.

CONCLUSIONS

Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment.

Tumor subtypes and signature model construction based on chromatin regulators for better prediction of prognosis in uveal melanoma

Background: Uveal Melanoma (UM) is the most prevalent primary intraocular malignancy in adults. This study assessed the importance of chromatin regulators (CRs) in UM and developed a model to predict UM prognosis. Methods: Gene expression data and clinical information for UM were obtained from public databases. Samples were typed according to the gene expression of CRs associated with UM prognosis. The prognostic key genes were further screened by the protein interaction network, and the risk model was to predict UM prognosis using the least absolute shrinkage and selection operator (LASSO) regression analysis and performed a test of the risk mode. In addition, we performed gene set variation analysis, tumor microenvironment, and tumor immune analysis between subtypes and risk groups to explore the mechanisms influencing the development of UM. Results: We constructed a signature model consisting of three CRs (RUVBL1, SIRT3, and SMARCD3), which was shown to be accurate, and valid for predicting prognostic outcomes in UM. Higher immune cell infiltration in poor prognostic subtypes and risk groups. The Tumor immune analysis and Tumor Immune Dysfunction and Exclusion (TIDE) score provided a basis for clinical immunotherapy in UM. Conclusion: The risk model has prognostic value for UM survival and provides new insights into the treatment of UM.

Comprehensive analysis of the role of ICOS ( CD278 ) in pan-cancer prognosis and immunotherapy

BACKGROUND

The immunological checkpoint known as Inducible T Cell Costimulatory Factor (ICOS, Cluster of Differentiation, CD278) is activated and expressed on T cells. Both somatic cells and antigen-presenting cells expressed its ligand, ICOSL (including tumor cells in the tumor microenvironment).It is important for immunosuppression. Uncertainty surrounds the function of ICOS in tumor immunity.

METHODS

Several bioinformatics techniques were employed by us to thoroughly examine the expression and prognostic value of ICOS in 33 cancers based on data collected from TCGA and GTEx. In addition, ICOS was explored with pathological stage, tumor-infiltrating cells, immune checkpoint genes, mismatch repair (MMR) genes, DNA methyltransferases (DNMTs), microsatellite instability (MSI),and tumor mutation burden (TMB).In addition,To ascertain the level of ICOS expression in various cells, qRT-PCR was employed.

RESULTS

The findings revealed that ICOS expression was up regulation in most cancer types. The high expression of ICOS in tumor samples was related to the poor prognosis of UVM and LGG; The positive prognosis was boosted by the strong expression of ICOS in OV, SARC, SKCM, THYM, UCEC, and HNSC. The result is that the expression of malignancy was revealed by the immune cells' invasion.profile of ICOS in different types of cancer. Different ways that ICOS expression is connected to immune cell infiltration account for variations in patient survival. Additionally, the TMB, MSI, MMR, and DNMT genes as well as ICOS expression are linked in many cancer types.The results of PCR showed that it is highly expressed in gastric, breast, liver and renal cell carcinoma cell lines compared with normal cells.

CONCLUSION

This study suggests that ICOS may be a potential tumor immunotherapy target and prognostic marker.

Multiple epigenetic modification profiles reveal the tumor immune microenvironment and clinical outcomes of uveal melanoma

Uveal melanoma (UM) is an aggressive intraocular cancer that, in 50% of cases, spreads to the patient's other systems. The exact cause of the increased metastatic rate is still unknown. Methylation and immune response, metastasis, and the expansion of cancer cells are closely related. Additionally, proteins linked to RNA methylation have come to light as possible cancer treatment targets. However, the relationship between methylation-related genes (MRGs) and the tumor microenvironment (TME) is still not understood. The goal of this work was to discover important MRGs and create a signature for UM patients' prognosis prediction. Using two different data sets, we examined the MRG expression patterns in the transcriptional and genomic regions of 106 UM samples. We discovered a connection between the clinicopathological traits of the patients, their prognosis, the capability of TME cells to infiltrate, and various MRG changes. Following that, we developed an MRGs signature to forecast prognosis, and we evaluated the model's precision in patients with UM. We grouped the patients into multiple categories based on their clinical traits, looked at the survival rates for various groups within various groupings, and tested their accuracy. Additionally, to increase the practical usability of the MRGs model, we created a very accurate nomogram. TIDE scores were higher in the low-risk group. We go over how MGRs could impact UM's TME, immunotherapy responsiveness, prognosis, and clinically significant features. We looked for different chemotherapeutic drugs and cutting-edge targeted agents for patients in diverse subgroups in order to better understand MRGs in UM. This helped in the creation of customized therapy to open new doors. We could also further research the prognosis and develop more efficient immunotherapy regimens.

Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data

Introduction

Uveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.

Methods

Based on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.

Results

The immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.

Discussion

The immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.

Cuproptosis key gene FDX1 is a prognostic biomarker and associated with immune infiltration in glioma

Recent studies have found that the protein encoded by the FDX1 gene is involved in mediating Cuproptosis as a regulator of protein lipoylation and related to immune response process of tumors. However, the specific biological function of FDX1 in glioma is currently unclear. To explore the potential function of FDX1, this study explored the correlation between the expression of FDX1 in cancers and survival prognosis by analyzing the public databases of GEPIA and Cbioportal. Immune infiltration was analyzed by the TIMER2.0 database in tumors. The possible biological processes and functions of FDX1-related in glioma were annotated through gene enrichment. Relationship between Cuproptosis and autophagy was explored through gene co-expression studies. Summary and conclusions of this study: (1) FDX1 is highly expressed in gliomas and associated with poor prognosis in low-grade gliomas (LGG). (2) Gene annotation indicates that FDX1 is mainly involved in the tumor protein lipoylation and cell death. (3) FDX1 expression is positively correlated with the infiltration of immune cells. (4) LIPT2 and NNAT, two other genes involved in lipoylation, may be unidentified marker gene for Cuproptosis. And the Cuproptosis genes related to FDX1 were positively correlated with the expression of autophagy marker genes Atg5, Atg12, and BECN-1. This evidence suggests that there may be some interaction between FDX1 mediated Cuproptosis and autophagy. In summary, FDX1 may serve as a potential immunotherapy target and prognostic marker for Glioma.

Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer

Background

The clinical outcomes of breast cancer (BC) are unpredictable due to the high level of heterogeneity and complex immune status of the tumor microenvironment (TME). When set up, multiple long non-coding RNA (lncRNA) signatures tended to be employed to appraise the prognosis of BC. Nevertheless, predicting immunotherapy responses in BC is still essential. LncRNAs play pivotal roles in cancer development through diverse oncogenic signal pathways. Hence, we attempted to construct an oncogenic signal pathway–based lncRNA signature for forecasting prognosis and immunotherapy response by providing reliable signatures.

Methods

We preliminarily retrieved RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and extracted lncRNA profiles by matching them with GENCODE. Following this, Gene Set Variation Analysis (GSVA) was used to identify the lncRNAs closely associated with 10 oncogenic signaling pathways from the TCGA-BRCA (breast-invasive carcinoma) cohort and was further screened by the least absolute shrinkage and selection operator Cox regression model. Next, an lncRNA signature (OncoSig) was established through the expression level of the final 29 selected lncRNAs. To examine survival differences in the stratification described by the OncoSig, the Kaplan–Meier (KM) survival curve with the log-rank test was operated on four independent cohorts (n = 936). Subsequently, multiple Cox regression was used to investigate the independence of the OncoSig as a prognostic factor. With the concordance index (C-index), the time-dependent receiver operating characteristic was employed to assess the performance of the OncoSig compared to other publicly available lncRNA signatures for BC. In addition, biological differences between the high- and low-risk groups, as portrayed by the OncoSig, were analyzed on the basis of statistical tests. Immune cell infiltration was investigated using gene set enrichment analysis (GSEA) and deconvolution tools (including CIBERSORT and ESTIMATE). The combined effect of the Oncosig and immune checkpoint genes on prognosis and immunotherapy was elucidated through the KM survival curve. Ultimately, a pan-cancer analysis was conducted to attest to the prevalence of the OncoSig.

Results

The OncoSig score stratified BC patients into high- and low-risk groups, where the latter manifested a significantly higher survival rate and immune cell infiltration when compared to the former. A multivariate analysis suggested that OncoSig is an independent prognosis predictor for BC patients. In addition, compared to the other four publicly available lncRNA signatures, OncoSig exhibited superior predictive performance (AUC = 0.787, mean C-index = 0.714). The analyses of the OncoSig and immune checkpoint genes clarified that a lower OncoSig score meant significantly longer survival and improved response to immunotherapy. In addition to BC, a high OncoSig score in several other cancers was negatively correlated with survival and immune cell infiltration.

Conclusions

Our study established a trustworthy and discriminable prognostic signature for BC patients with similar clinical profiles, thus providing a new perspective in the evaluation of immunotherapy responses. More importantly, this finding can be generalized to be applicable to the vast majority of human cancers.

The Multi-Omics Landscape and Clinical Relevance of the Immunological Signature of Phagocytosis Regulators: Implications for Risk Classification and Frontline Therapies in Skin Cutaneous Melanoma

Simple Summary

In this study, we focused on exploring phagocytosis regulators’ expression and mutational characteristics in skin cutaneous melanoma samples and delineating two molecular subtypes based on expression characteristics. We determined the relationship between phagocytosis regulators and survival by survival analysis of molecular subtypes. We then constructed a survival model (PRRS) to further quantify the criteria. Moreover, we combined pathway analysis, immune infiltration analysis, and mutation analysis to deeply explore the effects of phagocytosis regulators on skin cutaneous melanoma samples.

Abstract

Tumor-associated macrophages (TAMs) have gained considerable attention as therapeutic targets. Monoclonal antibody treatments directed against tumor antigens contribute significantly to cancer cell clearance by activating macrophages to phagocytose tumor cells. Due to its complicated genetic and molecular pathways, skin cutaneous melanoma (SKCM) has not yet attained the expected clinical efficacy and prognosis when compared to other skin cancers. Therefore, we chose TAMs as an entrance point. This study aimed to thoroughly assess the dysregulation and regulatory role of phagocytosis regulators in SKCM, as well as to understand their regulatory patterns in SKCM. This study subtyped prognosis-related phagocytosis regulators to investigate prognostic differences between subtypes. Then, we screened prognostic factors and constructed phagocytosis-related scoring models for survival prediction using differentially expressed genes (DEGs) between subtypes. Additionally, we investigated alternative treatment options using chemotherapeutic drug response data and clinical cohort treatment data. We first characterized and generalized phagocytosis regulators in SKCM and extensively examined the tumor immune cell infiltration. We created two phagocytosis regulator-related system (PRRS) phenotypes and derived PRRS scores using a principal component analysis (PCA) technique. We discovered that subtypes with low PRRS scores had a poor prognosis and decreased immune checkpoint-associated gene expression levels. We observed significant therapeutic and clinical improvements in patients with higher PRRS scores. Our findings imply that the PRRS scoring system can be employed as an independent and robust prognostic biomarker, serving as a critical reference point for developing novel immunotherapeutic methods.

Pyroptosis-Related Signature as Potential Biomarkers for Predicting Prognosis and Therapy Response in Colorectal Cancer Patients

Background: Abnormal mucosal inflammation is a critical risk factor for pathogenesis and progression of colorectal cancer (CRC). As a type of proinflammatory death, pyroptosis can recast a suitable microenvironment to promote tumor growth. However, the potential role of pyroptosis in CRC remains unclear.

Methods: A total of 38 pyroptosis-related gene (PRG) expression profiles and clinical information were collected from multiple public datasets. Bioinformatics methods were used to analyze the clinical significance, functional status, immune infiltration, genomic alteration, and drug sensitivity in different subgroups. Whole-genome microarray analysis was performed to analyze the regulation of gut microbiota on the expression of PRGs.

Results: Two distinct molecular subtypes were identified and suggested that multilayer PRG alterations were associated with patient clinicopathological features, prognosis, and tumor microenvironment (TME) infiltrating characteristics. Furthermore, we obtained eight PRG signatures by applying differential expression analysis and univariate Cox and Lasso regression analyses. A risk prognosis model was constructed for predicting overall survival (OS) and recurrence-free survival (RFS) based on the PRG signature. There were significant differences in clinical characteristics, 22 immune cells, and immune functions between the high- and low-risk groups. In addition, the PRG signature was significantly associated with the microsatellite instability (MSI), tumor mutation burden (TMB), cancer stem cell (CSC) index, immunotherapeutic characteristics, and chemotherapeutic drug sensitivity. Moreover, the in vitro experiments had shown that Fusobacterium nucleatum (F.n) could affect the CASP6 expression, which was associated with the chemoresistance to 5-fluorouracil (5-Fu) in CRC.

Conclusion: Our findings provided a foundation for future research targeting pyroptosis and a new insight into the prognosis and immune cell infiltration of CRC, and they suggested that F.n might influence CRC progression through pyroptosis.

PODNL1 Methylation Serves as a Prognostic Biomarker and Associates with Immune Cell Infiltration and Immune Checkpoint Blockade Response in Lower-Grade Glioma

Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.