Immune Infiltration Levels Research Articles

FUT11 expression in gastric cancer: its prognostic significance and role in immune regulation

BackgroundGastric cancer (GC) is a malignant digestive tract tumor with a high recurrence rate and poor prognosis. Fucosylation is important in tumor glycosylation, in which the key enzyme is fucosyltransferase (FUT). FUT11 is a member of the fucosyltransferase family and has been closely associated with the development of multiple cancers. However, the specific relationship between FUT11 and GC prognosis and its molecular mechanism has not been fully studied. This study explored FUT11 expression, clinical correlation, and its role in GC occurrence and development to deepen understanding of its function.MethodsFUT11 expression in 33 cancers was preliminarily analyzed using the Tumor Immunoassay Resource (TIMER2.0) database. FUT11 expression in GC was evaluated using The Cancer Genome Atlas stomach adenocarcinoma (TCGA-STAD) and Gene Expression Profiling Interactive Analysis (GEPIA2) data and verified using the Gene Expression Omnibus (GEO) GSE65801 dataset. Furthermore, we studied the survival prognosis of FUT11 in GC and analyzed its effect on the survival rate of patients with GC using the KM-plotter. We also performed COX regression analysis on TCGA GC clinical data and analyzed FUT11 expression in the pathway using the STRING and LinkedOmics databases. Moreover, the relationship between FUT11 and GC immune infiltration level was examined, and the Kaplan–Meier survival analysis diagram was constructed. The FUT11 genetic variation information was retrieved using cBioPortal, and its drug sensitivity was analyzed using CellMiner. Finally, differential FUT11 expression in GC tissues was verified using immunohistochemistry.ResultsThe data mining and analysis demonstrated that FUT11 expression was abnormally elevated in GC tissues and correlated with poor patient prognosis. The FUT11 expression level was an independent prognostic factor for GC. The difference in FUT11 expression level resulted in different degrees of immune cell infiltration in the patients with GC, which might regulate the tumor microenvironment. FUT11 affected GC development by participating in cancer pathways such as PI3K–AKT, neuroactive ligand–receptor, and MAPK. Immunohistochemical staining revealed that FUT11 was highly expressed in GC.ConclusionsThis study revealed that FUT11 expression is significantly increased in GC tissues. This increase is associated with poor prognosis and might affect immune regulation. FUT11 might have immunological and targeted therapeutic value, providing a new approach to GC treatment.

Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy

Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytosis in SCM. We identified six module genes (ATP11C, CD36, CEBPB, MAPK3, MAPKAPK2, PECAM1) strongly associated with SCM, leading to an accurate predictive model. Subgroups defined by EFFscore exhibited distinct clinical features and immune infiltration levels. Survival analysis showed that the C1 subtype with a lower EFFscore had better survival outcomes. scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from sepsis patients identified four genes (CEBPB, CD36, PECAM1, MAPKAPK2) associated with high EFFscores, highlighting their role in SCM. Molecular docking confirmed interactions between diagnostic genes and tamibarotene. Experimental validation supported our computational results. In conclusion, our study identifies a novel efferocytosis-related SCM subtype and diagnostic biomarkers, offering new insights for clinical diagnosis and therapy.

CTHRC1 is a prognostic biomarker correlated with immune infiltration in head and neck squamous cell carcinoma

BackgroundHead and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, characterized by high morbidity, high mortality, and poor prognosis. Collagen triple helix repeat containing 1 (CTHRC1) has been shown to be highly expressed in various cancers. However, its biological functions, potential role as a biomarker, and its relationship with immune infiltrates in HNSCC remain unclear. Our principal objective was to analyze CTHRC1 expression, its prognostic implications, biological functions, and its effects on the immune system in HNSCC patients using bioinformatics analysis.MethodsThe expression matrix was obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). CTHRC1 expression in HNSCC was analyzed between tumor and adjacent normal tissues, different stages were compared, and its impact on clinical prognosis was assessed using Kaplan-Meier analysis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA) were employed for enrichment analysis. The Search Tool for the Retrieval of Interacting Genes database (STRING) was used to analyze protein-protein interactions. Pearson correlation tests were used to investigate the association between CTHRC1 expression and immune checkpoints. The correlation between CTHRC1 and immune infiltration was investigated using CIBERSORT, TIMER, and ESTIMATE.ResultsCompared to adjacent normal tissues, CTHRC1 was found to be highly overexpressed in tumors. Increased expression of CTHRC1 was more evident in the advanced stage of HNSCC and predicted a poor prognosis. Most genes related to CTHRC1 in HNSCC were enriched in physiological functions of Extracellular matrix(ECM) and tumor. Furthermore, several immune checkpoints, such as TNFSF4 and CD276 have been shown to be associated with CTHRC1 expression. Notably, the level of CTHRC1 expression correlated significantly with immune infiltration levels, particularly activated macrophages in HNSCC.ConclusionsHigh expression of CTHRC1 predicts poor prognosis and is associated with immune infiltration in HNSCC, confirming its utility as a tumor marker for HNSCC.Trial registrationNot applicable. All data are from public databases and do not contain any clinical trials.

Identification of lncRNA-mRNA network linking ferroptosis and immune infiltration to colon adenocarcinoma suppression

BackgroundColon adenocarcinoma (COAD) is one of the most common malignant tumors. The interplay involving ferroptosis between tumor and immune cells plays a crucial in cancer progression. However, the biological basis of this interplay in COAD development remains elusive. MethodsTranscriptome data of COAD samples were obtained from The Cancer Genome Atlas and National Center for Biotechnology Information databases. Using single-sample gene set enrichment analysis, we calculated the ferroptosis score (FS) and immune cell infiltration levels for each sample, leveraging the expression levels of genes related to ferroptosis and various immune cell types. Samples with FSs greater than the 75th percentile were classified into the high-FS subgroup, while those below the 25th percentile were categorized as the low-FS subgroup. Moreover, tumor tissue samples and adjacent normal tissue samples were collected from twenty colon patients. Using real-time quantitative polymerase chain reaction, we validated the expression of certain genes in these samples. ResultsThe COAD samples with high FSs experienced favorable survival probability and heightened sensitivity to anticancer drugs, with FSs negatively associated with the pathological stages. Moreover, the up-regulated genes in high-FS subgroup exhibited enrichment in immune-related pathways, suggesting a correlation between immunity and ferroptosis. Importantly, we discovered a key lncRNA-mRNA co-expression network linking tumor cell ferroptosis and immune infiltration (e.g., neutrophil) in the progression and classification of COAD. Further analysis identified several ferroptosis-related lncRNAs (e.g., RP11-399O19.9) within this network, indicating their potential roles in COAD progression and deserving in-depth study. ConclusionsOur findings provide novel insights into the underlying biological basis, particularly involving lncRNAs, at gene expression level associated with ferroptosis in COAD and cancer therapy. Nevertheless, further analysis and validation are required to expand the findings.

Comprehensive analysis of cuproptosis-related genes involved in immune infiltration and their use in the diagnosis of hepatic ischemia‒reperfusion injury: an experimental Study.

Hepatic ischemia reperfusion injury (HIRI) is a common injury not only during liver transplantation but also during major hepatic surgery. HIRI causes severe complications and affects the prognosis and survival of patients. Cuproptosis, a newly identified form of cell death, plays an important role in a variety of illnesses. However, its role in HIRI remains unknown. The GSE151648 dataset was mined from the Gene Expression Omnibus (GEO) database, and differences were analyzed for intersections. Based on the differentially expressed genes (DEGs), functional annotation, differentially expressed cuproptosis-related genes (DE-CRGs) identification and lasso logistic regression were conducted. Correlation analysis of DE-CRGs and immune infiltration was further conducted, and DE-CRGs were applied to construct an HIRI diagnostic model. The hierarchical clustering method was used to classify the specimens of HIRI, and functional annotation was conducted to verify the accuracy of these DE-CRGs in predicting HIRI progression. The GSE14951 microarray dataset and GSE171539 single-cell sequencing dataset were chosen as validation datasets. At the same time, the significance of DE-CRGs was verified using a mouse model of HIRI with cuproptosis inhibitors and inducers. Finally, a network of transcription-factor-DE-CRGs and miRNA-DE-CRGs was constructed to reveal the regulation mechanisms. And potential drugs for DE-CRGs were predicted using Drug Gene Interaction Database (DGIdb). Overall, 2390 DEGs and 19 DE-CRGs were identified. Through machine learning algorithms, 8 featured DE-CRGs (GNL3, ALAS1, TSC22D2, KLF5, GTF2B, DNTTIP2, SLFN11 and HNRNPU) were screened, and 2 cuproptosis-related subclusters were defined. Based on the 8 DE-CRGs obtained from the HIRI model (AUC=0.97), the nomogram model demonstrated accuracy in predicting HIRI. Eight DE-CRGs were highly expressed in HIRI samples and were negatively related to immune cell infiltration. A higher level of immune infiltration and expression of CRG group B was found in the HIRI population. Differences in cell death and immune regulation were found between the 2 groups. The diagnostic value of the 8 DE-CRGs was confirmed in the validation of two datasets. The identification of 7 DE-CRGs (SLFN11 excluded) by HIRI animal model experiments was also confirmed. Using hTFtarget, miRWalk and DGIDB database, we predicted that 17 transcription factors, 192 miRNAs and 10 drugs might interact with the DE-CRGs. This study shows that cuproptosis may occur in HIRI and is correlated with immune infiltration. Additionally, a cuproptosis-related predictive model was constructed for studying the causes of HIRI and developing targeted treatment options for HIRI.

Construction of a circadian rhythm-relevant gene signature for hepatocellular carcinoma prognosis, immunotherapy and chemosensitivity prediction

AimsThis study explored the molecular and biologic mechanisms underlying the association between circadian rhythm disorders (CRD) and increased risk for hepatocellular carcinoma (HCC). BackgroundCRD are linked to increased risk for HCC, but the molecular and biologic mechanisms underlying this association are limited.ObjectiveThe study constructed and validated a CRD related gene model as an independent prognostic factor for HCC, providing insight into the molecular mechanisms linking CRD to increased HCC risk and identifying potential indicators for the efficacy of immunotherapy and anticancer drugs. This helps provide important clues for personalized treatment strategies for HCC patients. MethodsGene sets correlated with circadian rhythm were obtained from the Molecular Signatures Database (MSigDB) to intersect with differentially expressed genes (DEGs) between tumor samples and control samples in The Cancer Genome Atlas (TCGA) and HCCDB18 from Hepatocellular Carcinoma Cell DataBase (HCCDB). The CRD related gene model was developed by univariate Cox and stepwise multivariate analysis. Immune checkpoint blockade (ICB) therapy and anticancer drugs were analyzed using the tumor immune dysfunction and exclusion (TIDE) and pRRophetic, respectively. Seurat determined the cell type of HCC by analyzing single-cell data, and malignant cells were identified using Copykat. To detect the mRNA levels of genes in the CRD related gene model, quantitative real-time polymerase chain reaction (qRT-PCR) was carried out. ResultsThe activity of circadian rhythm in HCC tissue was significantly lower than that in control tissue. Subsequently, EZH2, IMPDH2, TYMS and SERPINE1 were selected to construct the CRD related gene model, which was an independent factor for HCC prognosis. Notably, low-risk patients had lower levels of immune cell infiltration and lower TIDE scores compared to high-risk patients with HCC, indicating that patients with a low risk may derive more benefit from immunotherapy. IMPDH2, TYMS and SERPINE1 expressed significantly higher in malignant cells than in benign epithelial cells. ConclusionsThis study presents a CRD related gene model to reveal the molecular perspective of the dependent mechanism of the association between CRD and cancer, which provides a potential indicator for understanding the preclinical efficacy of ICB and anticancer drugs.

Clinical, pathological and gene expression profiling of estrogen receptor discordance in breast cancer.

Breast cancer (BC) is the world's largest tumor species in which hormone receptor-positive patients have relatively good prognosis. However, majority of patients will develop late resistance, one of the important factors is due to the loss of the original estrogen receptor (ER) expression. We conducted this study in 115 patients with BC who experienced second biopsy at Jiangsu Province Hospital (JSPH) and divided patients into two subgroups ER + to - and ER + to + . First, clinicopathological characteristics between two groups were evaluated. Second, we explored candidate genes related to BC ER intratumor heterogeneity by applying next-generation sequencing (NGS) in 42 patients. Multi-omics integrative analysis of tumor transcriptomic, cancer-related pathway, diagnostic and prognostic value and immune profile were conducted. Besides, preliminary assay were also used to evaluate the correlation between KMT2C and ERα (ESR1) expression. The CCK-8, 5-Ethynyl-2'-deoxyuridine (EdU) assays, Transwell assays and the wound scratch tests were applied to explore the cellular interactions between KMT2C and BC. We find the histological type (p = 0.008) and disease-free survival (DFS) (p = 0.004) were significantly different in two subgroups. In Cox survival analysis, metastasis (Hazard ratio (HR) > 1, p = 0.007) and neo-adjuvant (HR < 1, p < 0.001) are independent prognostic factors of DFS. Besides, by analyzing NGS results, we found four genes KMT2C, FGFR19, FGF1 and FGF4 were highly mutated genes in ER + to - subgroup. Furthermore, the gene KMT2C displayed significant diagnostic value and prognostic value in BC and pan-cancer. In addition, a positive correlation between KMT2C expression and immune infiltrating levels of T cell CD4 + , macrophage and neutrophil was found. In the end, Western blot and RT-qPCR assay were used and found KMT2C and ERα (ESR1) expressions are strongly positive correlated in mRNA and protein level. Inhibition of KMT2C significantly reduced proliferation, invasion, and migration of MCF7 cells. People in two cohorts from JSPH presented different clinical characteristics and prognosis. The gene KMT2C may affect the progression of BC by regulating the molecular, epigenetic activity and immune infiltration. It may also serve as a novel prognostic biomarker for BC patients who underwent ER status converted from positive to negative.

Multi-omic validation of the cuproptosis-sphingolipid metabolism network: modulating the immune landscape in osteosarcoma.

The current understanding of the mechanisms by which metal ion metabolism promotes the progression and drug resistance of osteosarcoma remains incomplete. This study aims to elucidate the key roles and mechanisms of genes involved in cuproptosis-related sphingolipid metabolism (cuproptosis-SPGs) in regulating the immune landscape, tumor metastasis, and drug resistance in osteosarcoma cells. This study employed multi-omics approaches to assess the impact of cuproptosis-SPGs on the prognosis of osteosarcoma patients. Lasso regression analysis was utilized to construct a prognostic model, while multivariate regression analysis was applied to identify key core genes and generate risk coefficients for these genes, thereby calculating a risk score for each osteosarcoma patient. Patients were then stratified into high-risk and low-risk groups based on their risk scores. The ESTIMATE and CIBERSORT algorithms were used to analyze the level of immune cell infiltration within these risk groups to construct the immune landscape. Single-cell analysis was conducted to provide a more precise depiction of the expression patterns of cuproptosis-SPGs among immune cell subtypes. Finally, experiments on osteosarcoma cells were performed to validate the role of the cuproptosis-sphingolipid signaling network in regulating cell migration and apoptosis. In this study, seven cuproptosis-SPGs were identified and used to construct a prognostic model for osteosarcoma patients. In addition to predicting survival, the model also demonstrated reliability in forecasting the response to chemotherapy drugs. The results showed that a high cuproptosis-sphingolipid metabolism score was closely associated with reduced CD8 T cell infiltration and indicated poor prognosis in osteosarcoma patients. Cellular functional assays revealed that cuproptosis-SPGs regulated the LC3B/ERK signaling pathway, thereby triggering cell death and impairing migration capabilities in osteosarcoma cells. The impact of cuproptosis-related sphingolipid metabolism on the survival and migration of osteosarcoma cells, as well as on CD8 T cell infiltration, highlights the potential of targeting copper ion metabolism as a promising strategy for osteosarcoma patients.

Developing a prognostic model for skin melanoma based on the persistent tumor mutation burden and determining IL17REL as a therapeutic target

BackgroundOne popular and well-established marker for the immune checkpoint blockade (ICB) response is tumor mutation burden (TMB). Persistent TMB (pTMB), a subset of TMB, provides a better indicator to predict patient ICB therapy outcomes, as shown by some studies. Immune checkpoint drugs have significantly changed how melanoma is treated in recent years.MethodsIn this study, we integrated the TCGA-SKCM database and data of pTMB of TCGA from the paper that first mentioned pTMB and analyzed mutational and Immune characteristics associated with pTMB level in SKCM. Next, the predictive DEGs were identified the subgroups of pTMB by Cox regression and LASSO analyses to construct a pTMB-related signature. Finally, the expression and Biological functions of signature genes was detected, and further validated in vitro assay.ResultsIn the current research, we explored the mutational and immunological features related to the level of TMB in cutaneous melanoma (CM). The high-pTMB subgroup exhibited an increasing incidence of gene changes and higher levels of immune cell infiltration. Subsequently, we established a pTMB-related signature based on the predictive DEGs and found the biological features and immune-associated variables between two distinct risk groups. Lastly, the results of the clinical sample validation demonstrated that the expression of IL17REL was down-regulated in the collected samples of individuals with CM. The in vitro assay results indicated that IL17REL effectively suppressed the proliferation, clonality, and migration of CM cells.ConclusionIn conclusion, we have developed a prediction model associated with TMB and subsequently validated the potential influence of IL17REL on Overall Survival (OS) in patients diagnosed with melanoma.

Identification of a signature of histone modifiers in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is a cancer that is closely associated with epigenetic alterations, and histone modifiers (HMs) are closely related to epigenetic regulation. Therefore, this study aimed to comprehensively explore the function and prognostic value of HMs-based signature in KIRC. HMs were first obtained from top journal. Then, the mRNA expression profiles and clinical information in KIRC samples were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (Lasso) analysis were implemented to find prognosis-related HMs and construct a risk model related to the prognosis in KIRC. Kaplan-Meier analysis was used to determine prognostic differences between high- and low-risk groups. Immune infiltration and drug sensitivity analysis were also performed between high- and low-risk groups. Eventually, 8 HMs were successfully identified for the construction of a risk model in KIRC. The results of the correlation analysis between risk signature and the prognosis showed HMs-based signature has good prognostic value in KIRC. Results of immune analysis of risk models showed there were significant differences in the level of immune cell infiltration and expression of immune checkpoints between high- and low-risk groups. The results of the drug sensitivity analysis showed that the high-risk group was more sensitive to several chemotherapeutic agents such as Sunitinib, Tipifarnib, Nilotinib and Bosutinib than the low-risk group. In conclusion, we successfully constructed HMs-based prognostic signature that can predict the prognosis of KIRC.

Comprehensive bioinformatics analysis and cell line experiments revealed the important role of CDCA3 in sarcoma

BackgroundSarcoma mainly originate from bone and soft tissue and are highly aggressive malignant tumors. Cell division cycle-related protein 3 (CDCA3) is a protein involved in the regulation of the cell cycle, which is highly expressed in a variety of malignant tumors. However, its role in sarcoma remains unclear. This study aims to investigate the function and potential mechanism of CDCA3 in sarcoma and to elucidate its importance in sarcoma. MethodsWe first studied the expression and prognosis of CDCA family members in sarcoma by Oncomine and the Gene Expression Profiling Interactive Analysis (GEPIA). The role of CDCA3 protein in sarcoma was further analyzed by the Cancer Genome Atlas Program (TCGA), the Cancer Cell Lineage Encyclopedia (CCLE), and Linke-dOmics. In addition, immunohistochemistry and Western blot were used to verify the expression of CDCA3 protein in clinical samples as well as sarcoma cell lines (U2OS, SAOS2, MG63, and HOS). Subsequently, in vitro experiments (cloning and scratching experiments) were performed using sh-NC as well as sh-CDCA3 group cells to reveal the biological functions of CDCA3. ResultsWe found that the CDCA family (CDCA3, CDCA4, and CDCA8) is highly expressed in sarcoma, and the expression level of CDCA3, CDCA4, and CDCA8 negatively correlates with the prognosis of sarcoma patients. CDCA3 mRNA was highly expressed in pan-cancer by CCLE and TCGA database analysis. KEGG analysis showed that CDCA3 was mainly enriched in the cell cycle signaling pathway (It promoted the transition of the cell cycle from the G0/G1 phase to the S phase). In the level of immune infiltration, CDCA3 was negatively correlated with pDC cells, CD8+T cells, and cytotoxic cells. Finally, patients with high CDCA3 expression in sarcoma were analyzed for resistance to NU7441 and others, while sensitive to Fulvestrant and Dihydrorotenone. Furthermore, we demonstrated high expression of CDCA3 protein in sarcoma tissues and cell lines by immunohistochemistry and Western blot experiments. Cloning, EDU, scratching, and migration experiments showed that the knockdown of CDCA3 inhibited the Proliferation and progression of sarcoma cells. ConclusionThese results suggest for the first time that knockdown of CDCA3 may inhibit sarcoma progression. CDCA3 may be an effective target for the treatment of sarcoma.

Integration of mult-omics and nucleotide metabolism reprogramming signature analysis reveals gastric cancer immunological and prognostic features

BackgroundGastric cancer is a frequent and lethal solid tumor that has a poor prognosis and treatment result. Reprogramming of nucleotide metabolism is a characteristic of cancer development and progression.MethodsWe used a variety of machine learning techniques to create a novel nucleotide metabolism-related index (NMRI) using gastric cancer sample data obtained from the TCGA and GEO databases. This index is based on genes associated to nucleotide metabolism. Gastric cancer patients were categorized into high and low NMRI groups based on NMRI results. The clinical features, tumor immune microenvironment, response to chemotherapy, and response to immunotherapy were then thoroughly examined. In vitro experiments were then used to confirm the biological role of SERPINE1 in gastric cancer.ResultsThe four nucleotide metabolism-related genes that make up NMRI (GAMT, ORC1, CNGB3, and SERPINE1) were verified in an external dataset and are a valid predictor of prognosis for patients with gastric cancer. The high NMRI group was more responsive to immunotherapy and had greater levels of immune cell infiltration than the low NMRI group. The proliferation and migration of stomach cancer was shown to be decreased by SERPINE1 knockdown in vitro.ConclusionsThis study's NMRI can reliably predict a patient's prognosis for stomach cancer and pinpoint the patient group that will benefit from immunotherapy, offering important new information on the clinical treatment of stomach cancer.

Prediction of Prognosis in Patients with Sepsis Based on Platelet-Related Genes.

The study aimed to develop a risk prognostic model using platelet-related genes (PRGs) to predict sepsis patient outcomes. Sepsis patient data from the Gene Expression Omnibus (GEO) database and PRGs from the Molecular Signatures Database (MSigDB) were analyzed. Differential analysis identified 1139 differentially expressed genes (DEGs) between sepsis and control groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed enrichment in functions related to immune cell regulation and pathways associated with immune response and infectious diseases. A risk prognostic model was established using LASSO and Cox regression analyses, incorporating 10 PRGs selected based on their association with sepsis prognosis. The model demonstrated good stratification and prognostic effects, confirmed by survival and receiver operating characteristic (ROC) curve analyses. It served as an independent prognostic factor in sepsis patients. Further analysis using the CIBERSORT algorithm showed higher infiltration of activated natural killer (NK) cells and lower infiltration of CD8 T cells and CD4 T cells naïve in the high-risk group compared to the low-risk group. Additionally, expression levels of human leukocyte antigen (HLA) genes were significantly lower in the high-risk group. In conclusion, the 10-gene risk model based on PRGs accurately predicted sepsis patient prognosis and immune infiltration levels. This study provides valuable insights into the role of platelets in sepsis prognosis and diagnosis, offering potential implications for personalized treatment strategies.

A Subset of Microsatellite Unstable Cancer Genomes Prone to Short Insertions over Deletions Is Associated with Elevated Anticancer Immunity.

Deficiencies in DNA mismatch repair (MMRd) leave characteristic footprints of microsatellite instability (MSI) in cancer genomes. We used data from the Cancer Genome Atlas and International Cancer Genome Consortium to conduct a comprehensive analysis of MSI-associated cancers, focusing on indel mutational signatures. We classified MSI-high genomes into two subtypes based on their indel profiles: deletion-dominant (MMRd-del) and insertion-dominant (MMRd-ins). Compared with MMRd-del genomes, MMRd-ins genomes exhibit distinct mutational and transcriptomic features, including a higher prevalence of T>C substitutions and related mutation signatures. Short insertions and deletions in MMRd-ins and MMRd-del genomes target different sets of genes, resulting in distinct indel profiles between the two subtypes. In addition, indels in the MMRd-ins genomes are enriched with subclonal alterations that provide clues about a distinct evolutionary relationship between the MMRd-ins and MMRd-del genomes. Notably, the transcriptome analysis indicated that MMRd-ins cancers upregulate immune-related genes, show a high level of immune cell infiltration, and display an elevated neoantigen burden. The genomic and transcriptomic distinctions between the two types of MMRd genomes highlight the heterogeneity of genetic mechanisms and resulting genomic footprints and transcriptomic changes in cancers, which has potential clinical implications.

Upregulation of sperm-associated antigen 5 expression in endometrial carcinoma was associated with poor prognosis and immune dysregulation, and promoted cell migration and invasion

Sperm-associated antigen 5 (SPAG5) regulates cancer cell invasion and is involved in the progression of many cancers. However, the role of SPAG5 in endometrial carcinoma (EC) is still unknown. The purpose of this study was to explore the role of SPAG5 in EC and its potential molecular mechanism. The UALCAN tool and cBioPortal were used to analyze the expression and alterations of SPAG5 in EC, respectively. OncoLnc was used for survival analysis. We analyzed the effects of SPAG5 on immune cell infiltration and the expression levels of immune checkpoints. We also overexpressed and knocked down SPAG5 in EC cells to explore the effect of SPAG5 regulation on migration, invasion, apoptosis, and the cell cycle of EC cells. We found that SPAG5 was overexpressed and the SPAG5 gene was often mutated in EC. High SPAG5 expression was significantly associated with poor overall survival in patients with EC. SPAG5 also affected the level of immune cell infiltration in the TIME and the expression of immune checkpoints lymphocyte activating 3 (LAG3) and T cell immunoreceptor with Ig and ITIM domains (TIGIT) in patients with EC. It may also be involved in the immunotherapy response in these patients. In vitro experiments showed that SPAG5 promotes cancer cell migration and invasion. In conclusion, this study lays the foundation for further understanding the molecular mechanisms of EC involving SPAG5 and contributes to diagnosing and managing this disease.

Risk score constructed with neutrophil extracellular traps-related genes predicts prognosis and immune microenvironment in multiple myeloma.

Multiple myeloma (MM) exhibits considerable heterogeneity in treatment responses and survival rates, even when standardized care is administered. Ongoing efforts are focused on developing prognostic models to predict these outcomes more accurately. Recently, neutrophil extracellular traps (NETs) have emerged as a potential factor in MM progression, sparking investigation into their role in prognostication. In this study, a multi-gene risk scoring model was constructed using the intersection of NTEs and differentially expressed genes (DEGs), applying the least absolute shrinkage and selection operator (LASSO) Cox regression model. A nomogram was established, and the prognostic model's effectiveness was determined via Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were employed to evaluate the level of immune infiltration. The sensitivity of chemotherapy drugs was assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Ultimately, the presence of the detected genes was confirmed through quantitative real-time polymerase chain reaction (qRT-PCR) analysis in MM cell specimens. 64 NETs-DEGs were yielded, and through univariate Cox regression and LASSO regression analysis, we constructed a risk score composed of six genes: CTSG, HSPE1, LDHA, MPO, PINK1, and VCAM1. MM patients in three independent datasets were classified into high- and low-risk groups according to the risk score. The overall survival (OS) of patients in the high-risk group was significantly reduced compared to the low-risk group. Furthermore, the risk score was an independent predictive factor for OS. In addition, interactions between the risk score, immune score, and immune cell infiltration were investigated. Further analysis indicated that patients in the high-risk group were more sensitive to a variety of chemotherapy and targeted drugs, including bortezomib. Moreover, the six genes provided insights into the progression of plasma cell disorders. This study offers novel insights into the roles of NETs in prognostic prediction, immune status, and drug sensitivity in MM, serving as a valuable supplement and enhancement to existing grading systems.

Exploring the role of pyroptosis and immune infiltration in sepsis based on bioinformatic analysis

PurposeSepsis is a disease that is typically treated in intensive care units with high mortality and morbidity. Pyroptosis is a newly identified type of programmed cell death and is characterized by inflammatory cytokine secretion. However, the role of pyroptosis in sepsis remains unclear. MethodsGSE28750 and GSE134347 datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed pyroptosis genes (DEPGs) were identified between sepsis and healthy controls. Machine learning was used to further narrow the gene range. Receiver operating curves (ROC) were generated to estimate the diagnostic efficacy. Immune infiltration levels were estimated via single-sample gene set enrichment analysis (ssGSEA). A network database was used to predict the upstream transcription factors and miRNAs of DEPGs. Finally, the expression of the genes was validated by qRT-PCR between sepsis patients and healthy controls. ResultsWe found that the pyroptosis pathway was enriched and activated in sepsis. 8 DEPGs were identified. A heatmap showed that the genes, NLRC4, NAIP, IL-18, AIM2 and ELANE, were abundant in the sepsis samples, and the genes, NLRP1, CHMP7 and TP53, were abundant in the healthy control samples. The ssGSEA results showed that the abundances of activated dendritic cells, MDSC, macrophage, plasmacytoid dendritic cells, regulatory T-cells, and Th17-cells were significantly higher, while the activated B-cell, activated CD8 T-cell, CD56 dim tural killer cell, immature B-cell, monocyte, and T follicular helper cell abundances were lower in sepsis samples compared to healthy controls. The qRT-PCR results showed that the expression levels of NAIP, IL-18, TP53, CHMP7, NLRC4, ELANE and NLRP1 were consistant with the bioinformatic analyses, while the expression level of AIM2 has no significant difference. ConclusionOur study identified seven potential pyroptosis-related genes, NAIP, IL-18, TP53, CHMP7, NLRC4, ELANE and NLRP1. This study revealed that pyroptosis may promote sepsis development by activating the immune response.

Identification of tumor-antigen signatures and immune subtypes for messenger RNA vaccine selection in advanced clear cell renal cell carcinoma

BackgroundAdvanced clear cell renal cell carcinoma still lacks reliable diagnostic and prognostic biomarkers. Recently, tumor vaccines targeting specific molecules have been proposed as a promising treatment in mitigating tumor progression, which was rekindled under the background of the COVID-19 pandemic. However, the application of messenger RNA vaccine against advanced clear cell renal cell carcinoma antigens remains stagnant, and no subgroup of patients deemed suitable for vaccination has been extensively studied or validated. Our study aims to explore novel advanced clear cell renal cell carcinoma antigen signatures to select suitable patients for vaccination. MethodsGene expression profiles of advanced clear cell renal cell carcinoma samples and their corresponding clinical data were retrieved from The Cancer Genome Atlas. The least absolute shrinkage and selection operator model was applied to develop signatures to stratify patients with advanced clear cell renal cell carcinoma. Receiver operating characteristic analysis was used to compare the prognostic accuracy of each factor. Tumor Immune Estimation Resource was used to visualize the relationship between the proportion of antigen-presenting cells and the expression of filtered genes. The "CIBERSORT" and "WGCNA" R Packages were employed to ascertain disparities in immune infiltration levels between advanced clear cell renal cell carcinoma subgroups. The Search Tools for the Retrieval of Interacting Genes database and Cytoscape were used to construct the protein-protein interaction network. CCK-8 and colony formation assays were included in the invitro experiment. ResultsIn total, 244 potential tumor antigens were identified. Using the least absolute shrinkage and selection operator Cox regression, 21 tumor antigens were selected for developing a risk evaluation signature. The risk score signature can be a useful tool to predict the outcome of advanced clear cell renal cell carcinoma patients. According to the differential clinical, molecular, and immune-related genes, we divided advanced clear cell renal cell carcinoma patients into the immune “cold” subtype and immune “hot” subtype. By developing a logistic score, the immune subtype signature can better distinguish a patient more likely to be immune “cold” subtype or immune “hot” subtype.Interestingly, patients with high risk scores had a higher proportion of immune “hot” subtype than those with a low risk score. Furthermore, the prognostic value was significantly improved when combining risk score and immune subtype. Distinct immune landscapes and signal pathways were observed between different tumor subtypes. Finally, novel tumor antigens related to oxidative stress were identified. ConclusionThe tumor-antigens–based risk score and immune subtype signatures identified potentially effective neo-antigens for advanced clear cell renal cell carcinoma messenger RNA vaccine development, and patients with low risk scores and immune “cold” subtype tumors are more prone to benefit from messenger RNA vaccination. Furthermore, our study highlights the significant role of oxidative stress in determining the efficacy of the messenger RNA vaccine.

Efficacy of immunotherapy in ARID1A-mutant solid tumors: a single-center retrospective study

BackgroundImmune checkpoint inhibitors (ICIs), especially those targeting programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), have introduced a new treatment landscape for many types of tumors. However, they only achieve a limited therapeutic response. Hence, identifying patients who may benefit from ICIs is currently a challenge.Methods47 tumor patients harboring ARID1A mutations were retrospectively studied. The genomic profiling data through next-generation sequencing (NGS) and relevant clinical information were collected and analyzed. Additionally, bioinformatics analysis of the expression of immune checkpoints and immune cell infiltration levels was conducted in ARID1A-mutant gastric cancer (GC).ResultsARID1A mutations frequently co-occur with mutations in DNA damage repair (DDR)-associated genes. Among the 35 ARID1A-mutant patients who received immunotherapy, 27 were evaluable., with the objective response rate (ORR) was 48.15% (13/27), and the disease control rate (DCR) was 92.59% (25/27). Moreover, survival assays revealed that ARID1A-mutant patients had longer median overall survival (mOS) after immunotherapy. In ARID1A-mutated GC patients, receiving ICIs treatment indicated longer progressive-free survival (PFS). Additionally, the incidence of microsatellite instability-high (MSI-H), high tumor mutation burden (TMB-H) and Epstein‒Barr virus (EBV) infection was elevated. Bioinformatic analysis showed significant enrichment of immune response and T cell activation pathway within differentially expressed genes in ARID1A-mutant GC group. Finally, ARID1A mutations status was considered to be highly correlated with the level of tumor infiltrating lymphocytes (TILs) and high expression of immune checkpoints.ConclusionsPatients with tumors harboring ARID1A mutations may achieve better clinical outcomes from immunotherapy, especially in GC. ARID1A mutations can lead to genomic instability and reshape the tumor immune microenvironment (TIME), which can be used as a biomarker for immunotherapy.

Comprehensive analysis of signaling lymphocyte activation molecule family as a prognostic biomarker and correlation with immune infiltration in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is a common type of kidney cancer and accounts for 2-3% of all cancer cases. Furthermore, a growing number of immunotherapy approaches are being used in antitumor treatment. Signaling lymphocyte activation molecule family (SLAMF) members have been well studied in several cancers, whereas their roles in ccRCC have not been investigated. The present study comprehensively assessed the molecular mechanisms of SLAMF members in ccRCC, performed using The Cancer Genome Atlas database, with analysis of gene transcription, prognosis, biological function, clinical features, tumor-associated immune cells and the correlation with programmed cell death protein 1/programmed death-ligand 1 immune checkpoints. Simultaneously, the Tumor Immune Dysfunction and Exclusion algorithm was used to predict the efficacy of immune checkpoint blockade (ICB) therapy in patients with high and low SLAMF expression levels. The results demonstrated that all SLAMF members were highly expressed in ccRCC, and patients with high expression levels of SLAMF1, 4, 7 and 8 had a worse prognosis that those with low expression. SLAMF members were not only highly associated with immune activation but also with immunosuppressive agents. The level of immune cell infiltration was associated with the prognosis of patients with ccRCC with high SLAMF expression. Moreover, high ICB response rates were observed in patients with high expression levels of SMALF1 and 4. In summary, SLAMF members may serve as future potential biomarkers for predicting the prognosis of ccRCC and emerge as a novel immunotherapy target.