Immune Cell Infiltration Levels Research Articles

Systematic analysis of DNA methylation-mediated TF dysregulation on lncRNAs reveals critical roles in tumor immunity

Emerging evidence suggests that DNA methylation affects transcriptional regulation and expression perturbations of long non-coding RNAs (lncRNAs) in cancer. However, a comprehensive investigation into the transcriptional control of DNA methylation-mediated dysregulation of transcription factors (TFs) on lncRNAs has been lacking. Here, we integrated the transcriptome, methylome, and regulatome across 21 human cancers and systematically identified the transcriptional regulation of DNA methylation-mediated TF dysregulations (DMTDs) on lncRNAs. Our findings reveal that TF regulation of lncRNAs is significantly impacted by DNA methylation. Comparative analysis of DMTDs on mRNAs revealed a conserved pattern of TFs involvement. Pan-cancer Methylation TFs (MethTFs) and Methylation LncRNAs (MethLncRNAs) were identified, and were found to be closely associated with cancer hallmarks and clinical features. In-depth analysis of co-expressed mRNAs with pan-cancer MethLncRNAs unveiled frequent disruptions in cancer immunity, particularly in the context of inflammatory response. Furthermore, we identified five immune-related network modules that contribute to immune cell infiltration in cancer. Immune-related subtypes were subsequently classified, characterized by high levels of immune cell infiltration, expression of immunomodulatory genes, and relevant immune cytolytic activity score, major histocompatibility complex score, response to chemotherapy, and prognosis. Our findings provide valuable insights into cancer immunity from the epigenetic and transcriptional regulation perspective.

Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma.

Copper and copper-binding proteins are key components of tumor progression as they play important roles in tumor invasion and migration, but their associations in gliomas remain unclear. Transcriptomic datasets of glioblastoma, low-grade glioma, and normal brain cortex were derived from the TCGA and GTEX databases. Differentially expressed genes (DEGs) of copper-binding proteins were screened and used to construct a prognostic model based on COX and LASSO regression, which was further validated by the CGGA datasets. The expressions of risk-model genes were selectively confirmed via anatomic feature-based expression analysis and immunohistochemistry. The risk score was stratified by age, gender, WHO grade, IDH1 mutation, MGMT promoter methylation, and 1p/19q codeletion status, and a nomogram was constructed and validated. A total of 21 DEGs of copper-binding proteins were identified and a six-gene risk-score model was constructed, consisting of ANG, F5, IL1A, LOXL1, LOXL2, and STEAP3, which accurately predicted 1-, 3-, and 5-year overall survival rates, with the AUC values of 0.87, 0.88, and 0.82, respectively. The high-risk group had a significantly shorter OS (p < 0.0001) and was associated with old age, wild-type IDH1, a high WHO grade, an unmethylated MGMT promoter, and 1p/19q non-codeletion and had higher levels of immune cell infiltration, cancer-immunity suppressor, and immune checkpoint gene expression as well as a higher TMB. The model based on the genes of copper-binding proteins could contribute to prognosis prediction and provide potential targets against gliomas.

DLAT is a promising prognostic marker and therapeutic target for hepatocellular carcinoma: a comprehensive study based on public databases

Cuproptosis is a new mechanism of cell death that differs from previously identified regulatory cell death mechanisms. Cuproptosis induction holds promise as a new tumour treatment. Therefore, we investigated the value of cuproptosis-related genes in the management of hepatocellular carcinoma (HCC). The cuproptosis-related gene Dihydrolipoamide S-Acetyltransferase (DLAT) were significantly upregulated in liver cancer tissues. High levels of DLAT were an independent prognostic factor for shorter overallsurvival (OS) time. DLAT and its related genes were mainly involved in cell metabolism, tumor progression and immune regulation. DLAT was significantly associated with the level of immune cell infiltration and immune checkpoints in HCC. HCC with high DLAT expression was predicted to be more sensitive to sorafenib treatment. The risk prognostic signature established based on DLAT and its related genes had a good prognostic value. The cuproptosis-related gene DLAT is a promising independent prognostic marker and therapeutic target in HCC. The new prognostic signature can effectively predict the prognosis of HCC patients.

Comprehensive Analysis of the Relationship between Cuproptosis-Related Gene GCSH and Prognosis, Tumor Microenvironment Infiltration, and Therapy Response in Endometrial Cancer

Introduction: Cuproptosis is a novel form of cell death regulated by protein lipoylation and implicated in mitochondrial metabolism. However, further research is needed to explore the influence of the cuproptosis-related gene γ-glutamylcysteine synthetase (GCSH) on the prognosis of endometrial cancer (EC), the tumor immune microenvironment, and therapeutic response. Methods: The differential expression of GCSH between EC and normal tissues was analyzed using multiple public databases. Additionally, cancer and adjacent tissues were prospectively collected from 17 EC patients, and immunohistochemical analysis was performed to further investigate GCSH expression differences. The relationship between GCSH and the prognosis and clinicopathological characteristics of EC patients was evaluated, and a nomogram was constructed to predict patient survival based on GCSH expression. Subsequently, Gene set variation analysis was used to explore the potential biological functions of GCSH in EC. The impact of GCSH on the tumor microenvironment (TME) was estimated. Finally, the effect of GCSH on the response to immunotherapy and chemotherapeutic drugs in EC was investigated. Results: The expression of GCSH was significantly upregulated in EC. High GCSH expression was associated with poor prognosis in EC patients. Enrichment analysis revealed an association between high GCSH and immune suppression. Furthermore, high GCSH was found to be associated with a non-inflamed TME, leading to decreased infiltration levels of immune cells. Lastly, it was observed that patients with high GCSH exhibited insensitivity to both immunotherapy and chemotherapeutic drugs. Conclusion: This study revealed the role of GCSH in TME, response to therapy, and clinical prognosis in EC, which provided novel insights for the therapeutic application in EC.

Pan-cancer genetic analysis of disulfidptosis-related gene set

BackgroundA recent study has identified a novel programmed cell death pathway, termed disulfidptosis, which is based on disulfide proteins. This discovery provides new insight into the mechanisms of cell death and may have implications for therapeutic strategies targeting cell death pathways. This study aimed to evaluate the pan-cancer genomics and clinical association of disulfidptosis and disulfidptosis-related cell death genes, including SLC7A11, INF2, CD2AP, PDLIM1, ACTN4, MYH9, MYH10, IQGAP1, FLNA, FLNB, TLN1, MYL6, ACTB, DSTN, and CAPZB. MethodsUsing multi-omics profiling data, this study provides a comprehensive and systematic characterization of disulfidptosis genes across more than 9000 samples of over 30 types of cancer. ResultsFLNA and FLNB were the two most frequently mutated disulfidptosis cell death genes in cancer. UCEC and SKCM were the two cancer types that have the highest mutation rates while the mutation of ACTN4 was associated with worse survival of CESC and ESCA. Breast cancer was potentially affected by disulfidptosis because its subtypes are different in disulfidptosis gene expression. Similarly, KIRC might also be associated with disulfidptosis. Additionally, the association of disulfidptosis-related cell death genes with survival was analyzed, with MESO and LGG as the top cancer types with survival associated with disulfidptosis cell death genes. The correlation between CNV and survival across multiple cancer types found that UCEC, KIRP, LGG, and KIRC were the top cancer types where the CNV level was associated with survival. There was a negative correlation between expression and methylation for most of the genes and there was only a slight correlation between methylation levels and survival of cancer in LGG. About half of the disulfidptosis-related cell death proteins were associated with the activation of EMT. Disulfidptosis genes were correlated to immune cell infiltration levels in cancers. Multiple compounds were identified as potential drugs that might be affected by disulfidptosis-related cell death for future study. ConclusionDisulfidptosis cell death genes are potentially involved in many cancer types and can be developed as candidates for cancer diagnosis, prognosis, and therapeutic biomarkers.

Identification of osteoarthritis-characteristic genes and immunological micro-environment features through bioinformatics and machine learning-based approaches

BackgroundOsteoarthritis (OA) is a multifaceted chronic joint disease characterized by complex mechanisms. It has a detrimental impact on the quality of life for individuals in the middle-aged and elderly population while also imposing a significant socioeconomic burden. At present, there remains a lack of comprehensive understanding regarding the pathophysiology of OA. The objective of this study was to examine the genes, functional pathways, and immune infiltration characteristics associated with the development and advancement of OA.MethodsThe Gene Expression Omnibus (GEO) database was utilized to acquire gene expression profiles. The R software was employed to conduct the screening of differentially expressed genes (DEGs) and perform enrichment analysis on these genes. The OA-characteristic genes were identified using the Weighted Gene Co-expression Network Analysis (WGCNA) and the Lasso algorithm. In addition, the infiltration levels of immune cells in cartilage were assessed using single-sample gene set enrichment analysis (ssGSEA). Subsequently, a correlation analysis was conducted to examine the relationship between immune cells and the OA-characteristic genes.ResultsA total of 80 DEGs were identified. As determined by functional enrichment, these DEGs were associated with chondrocyte metabolism, apoptosis, and inflammation. Three OA-characteristic genes were identified using WGCNA and the lasso algorithm, and their expression levels were then validated using the verification set. Finally, the analysis of immune cell infiltration revealed that T cells and B cells were primarily associated with OA. In addition, Tspan2, HtrA1 demonstrated a correlation with some of the infiltrating immune cells.ConclusionsThe findings of an extensive bioinformatics analysis revealed that OA is correlated with a variety of distinct genes, functional pathways, and processes involving immune cell infiltration. The present study has successfully identified characteristic genes and functional pathways that hold potential as biomarkers for guiding drug treatment and facilitating molecular-level research on OA.

Construction of a novel disulfidptosis-related signature for improving outcomes in hepatocellular carcinoma: Observational study.

Disulfidptosis is a novel form of metabolic-related regulated cell death (RCD) that is caused by disulfide stress caused by the accumulation of excess cystine in the cell. Targeting disulfide metabolism imbalance is an emerging strategy for the treatment of cancer. However, it is undetermined how disulfidptosis-related genes (DRGs) influence hepatocellular carcinoma (HCC). Unsupervised clustering analysis was performed on the TCGA-LIHC cohort to identify various phenotypes of disulfidptosis. GSVA was used to measure the activation of characteristic gene sets, while CIBERSORT was employed to estimate the infiltration of immune cells. Disulfidptosis-related signature was generated to quantify the phenotype of disulfidptosis in HCC patients. Next, we examined the disparities among the high and low disulfidptosis score categories by considering clinical characteristics, infiltration of immune cells, functions related to the immune system, sensitivity to chemotherapeutic drugs, and effectiveness of immunotherapy. Two different disulfidptosis phenotypes with different prognoses, clinical traits, biological pathways, and immune cell infiltration were identified. Based on differently expressed genes (DEGs) among 2 disulfidptosis phenotypes, a disulfidptosis-related signature was built. The prognostic value of this signature was then evaluated in the TCGA and GEO datasets. Low disulfidptosis score indicated favorable clinical outcomes, higher levels of immune cell infiltration, lower tumor purity, and enhanced immune responses. Furthermore, we noticed a clear disparity in tumor mutation load and drug responsiveness when comparing the high and low disulfidptosis score categories. Finally, a quantitative nomogram was built with disulfidptosis score and several clinical characteristics. The disulfidptosis-related signature provides new insights into the tumor immune microenvironment and complexity in HCC. The disulfidptosis score can serve as a promising tool for personalized prognostic prediction of HCC patients and for customizing more effective immunotherapeutic strategies.

Prognostic risk of immune-associated signature in the microenvironment of brain gliomas.

Understanding the key factors in the tumor microenvironment (TME) that affect the prognosis of gliomas is crucial. In this study, we sought to uncover the prognostic significance of immune cells and immune-related genes in the TME of gliomas. We incorporated data of 970 glioma patient samples from the Chinese Glioma Genome Atlas (CGGA) database as the training set, and an additional set of 666 samples from The Cancer Genome Atlas (TCGA) database served as the validation set. From our analysis, we identified 21 immune-related differentially expressed genes (DEGs) in the TME, which holds implications for glioma prognosis. Based on these genes, we constructed a prognostic risk model on the 21 genes. The prognostic risk model demonstrated robust performance with an area under the curve (AUC) value of 0.848. Notably, the risk score derived from the model emerged as an independent prognostic factor of gliomas, with high risk scores indicative of an unfavorable prognosis. Furthermore, we observed that high infiltration levels of certain immune cells, namely, activated dendritic cells, M0 macrophages, M2 macrophages, and regulatory T cells (Tregs), correlated with an unfavorable glioma prognosis. In conclusion, our findings suggested that the TME of gliomas harbored a distinct immune-associated signature, comprising 21 immune-related genes and specific immune cells. These elements significantly influence the prognosis and present potential as novel indicators in the clinical assessment of glioma patient outcomes.

Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer.

Colorectal cancer (CRC) is a common malignant tumor that severely endangers human health. Exosomes show great potential in tumor immunotherapy. Increasingly studies have shown that exosome-related genes are effective prognostic biomarkers. Clinical information and gene expression data of CRC patients were obtained from gene expression omnibus and the cancer genome atlas. The data were then classified into training and independent validation sets. In the training set, exosome-related genes with a prognostic value were selected by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression model, and stepwise Cox regression analysis. Risk scores were calculated based on the selected genes to stratify patients. The selected exosome-related genes were applied to establish a risk model. Based on 11 exosome-related genes, a prognostic risk model, which could stratify the risk both in the training and validation sets, was established. According to the survival curves, the prognoses of the high- and low-risk groups were significantly different. The AUCs of the risk model for prognostic prediction were 0.735 and 0.784 in the training and validation sets, respectively. A nomogram was constructed to predict the survival of CRC patients. Single-sample gene set enrichment analysis and ESTIMATE algorithms revealed that the risk model was related to immune cell infiltration. The value of the risk model in predicting immunotherapeutic outcomes was also confirmed. An exosome-related gene risk model was constructed to predict prognosis, evaluate microenvironment immune cell infiltration levels and bring a new perspective to CRC patient treatment.

Bioinformatics-based analysis of the roles of basement membrane-related gene AGRN in systemic lupus erythematosus and pan-cancer development.

Systemic lupus erythematosus (SLE) is an autoimmune disease involving many systems and organs, and individuals with SLE exhibit unique cancer risk characteristics. The significance of the basement membrane (BM) in the occurrence and progression of human autoimmune diseases and tumors has been established through research. However, the roles of BM-related genes and their protein expression mechanisms in the pathogenesis of SLE and pan-cancer development has not been elucidated. In this study, we applied bioinformatics methods to perform differential expression analysis of BM-related genes in datasets from SLE patients. We utilized LASSO logistic regression, SVM-RFE, and RandomForest to screen for feature genes and construct a diagnosis model for SLE. In order to attain a comprehensive comprehension of the biological functionalities of the feature genes, we conducted GSEA analysis, ROC analysis, and computed levels of immune cell infiltration. Finally, we sourced pan-cancer expression profiles from the TCGA and GTEx databases and performed pan-cancer analysis. We screened six feature genes (AGRN, PHF13, SPOCK2, TGFBI, COL4A3, and COLQ) to construct an SLE diagnostic model. Immune infiltration analysis showed a significant correlation between AGRN and immune cell functions such as parainflammation and type I IFN response. After further gene expression validation, we finally selected AGRN for pan-cancer analysis. The results showed that AGRN's expression level varied according to distinct tumor types and was closely correlated with some tumor patients' prognosis, immune cell infiltration, and other indicators. In conclusion, BM-related genes play a pivotal role in the pathogenesis of SLE, and AGRN shows immense promise as a target in SLE and the progression of multiple tumors.

Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes

Objectives The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD). Materials and Methods With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted. Results A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD. Conclusion Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.

Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer

HER2-positive (HER2+) breast cancer accounts for 20–25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical trial (ICORG10–05/NCT01485926) whole exome DNA sequencing was carried out on normal-tumour pairs collected from 22 patients. Here we report predictive modelling of neoadjuvant therapy response using clinicopathological and genomic features of pre-treatment tumour biopsies identified age, estrogen receptor (ER) status and level of immune cell infiltration may together be important for predicting response. Clonal evolution analysis of longitudinally collected tumour samples show subclonal diversity and dynamics are evident with potential therapy resistant subclones detected. The sources of greater pre-treatment immunogenicity associated with a pathological complete response is largely unexplored in HER2+ tumours. However, here we point to the possibility of APOBEC associated mutagenesis, specifically in the ER-neg/HER2+ subtype as a potential mediator of this immunogenic phenotype.

A Disulfidptosis-Related Gene Signature Associated with Prognosis and Immune Cell Infiltration in Osteosarcoma.

Osteosarcoma (OS) stands as a leading aggressive bone malignancy that primarily affects children and adolescents worldwide. A recently identified form of programmed cell death, termed Disulfidptosis, may have implications for cancer progression. Yet, its role in OS remains elusive. To elucidate this, we undertook a thorough examination of Disulfidptosis-related genes (DRGs) within OS. This involved parsing expression data, clinical attributes, and survival metrics from the TARGET and GEO databases. Our analysis unveiled a pronounced association between the expression of specific DRGs, particularly MYH9 and LRPPRC, and OS outcome. Subsequent to this, we crafted a risk model and a nomogram, both honed for precise prognostication of OS prognosis. Intriguingly, risks associated with DRGs strongly resonated with immune cell infiltration levels, myriad immune checkpoints, genes tethered to immunotherapy, and sensitivities to systematic treatments. To conclude, our study posits that DRGs, especially MYH9 and LRPPRC, hold potential as pivotal architects of the tumor immune milieu in OS. Moreover, they may offer predictive insights into treatment responses and serve as reliable prognostic markers for those diagnosed with OS.

A pan-cancer analysis reveals the diagnostic and prognostic role of CDCA2 in low-grade glioma.

Cell division cycle associated 2 (CDCA2), a member of the cell division cycle associated proteins (CDCA) family, is crucial in the regulation of cell mitosis and DNA repair. CDCA2 was extensively examined in our work to determine its role in a wide range of cancers. CDCA2 differential expression was studied in pan-cancer and in diverse molecular and immunological subgroups in this research. Additionally, the diagnostic and prognostic significance of CDCA2 in pan-cancer was also evaluated using receiver operating characteristic (ROC) and Kaplan-Meier (KM) curves. Prognostic value of CDCA2 in distinct clinical subgroups of lower grade glioma (LGG) was also investigated and a nomogram was constructed. Lastly, potential mechanisms of action of CDCA2 were interrogated including biological functions, ceRNA networks, m6A modification and immune infiltration. CDCA2 is shown to be differentially expressed in a wide variety of cancers. Tumors are diagnosed and forecasted with a high degree of accuracy by CDCA2, and the quantity of expression CDCA2 is linked to the prognosis of many cancers. Additionally, the expression level of CDCA2 in various subgroups of LGG is also closely related to prognosis. The results of enrichment analyses reveal that CDCA2 is predominantly enriched in the cell cycle, mitosis, and DNA replication. Subsequently, hsa-miR-105-5p is predicted to target CDCA2. In addition, 4 lncRNAs were identified that may inhibit the hsa-miR-105-5p/CDCA2 axis in LGG. Meanwhile, CDCA2 expression is shown to be associated to m6A-related genes and levels of immune cell infiltration in LGG. CDCA2 can serve as a novel biomarker for the diagnosis and prognosis in pan-cancer, especially in LGG. For the development of novel targeted therapies in LGG, it may be a potential molecular target. However, to be sure, we'll need to do additional biological experiments to back up our results from bioinformatic predictions.

Multi-omics approaches identify novel prognostic biomarkers of autophagy in uveal melanoma.

Uveal melanoma (UVM) is a rare yet malignant ocular tumor that metastases in approximately half of all patients, with the majority of those developing metastasis typically succumbing to the disease within a year. Hitherto, no effective treatment for UVM has been identified. Autophagy is a cellular mechanism that has been suggested as an emerging regulatory process for cancer-targeted therapy. Thus, identifying novel prognostic biomarkers of autophagy may help improve future treatment. Consensus clustering and similarity network fusion approaches were performed for classifying UVM patient subgroups. Weighted correlation network analysis was performed for gene module screening and network construction. Gene set variation analysis was used to evaluate the autophagy activity of the UVM subgroups. Kaplan-Meier survival curves (Log-rank test) were performed to analyze patient prognosis. Gene set cancer analysis was used to estimate the level of immune cell infiltration. In this study, we employed multi-omics approaches to classify UVM patient subgroups by molecular and clinical characteristics, ultimately identifying HTR2B, EEF1A2, FEZ1, GRID1, HAP1, and SPHK1 as potential prognostic biomarkers of autophagy in UVM. High expression levels of these markers were associated with poorer patient prognosis and led to reshaping the tumor microenvironment (TME) that promotes tumor progression. We identified six novel potential prognostic biomarkers in UVM, all of which are associated with autophagy and TME. These findings will shed new light on UVM therapy with inhibitors targeting these biomarkers expected to regulate autophagy and reshape the TME, significantly improving UVM treatment outcomes.

Identification of lactate regulation pattern on tumor immune infiltration, therapy response, and DNA methylation in diffuse large B-cell lymphoma.

Lactate, produced through glycolytic metabolism in the tumor microenvironment (TME), is implicated in tumorigenesis and progression in diverse cancers. However, the impact of lactate on the remodeling of the TME in diffuse large B-cell lymphoma (DLBCL) and its implications for therapy options remain unclear. A lactate-related (LAR) scoring model was constructed in DLBCL patients using bioinformatic methods. CIBERSORT, XCELL, and ssGSEA algorithms were used to determine the correlation between LAR score and immune cell infiltration. Tumor Immune Dysfunction and Exclusion (TIDE), rituximab, cyclophosphamide, adriamycin, vincristine, and prednisone (R-CHOP) cohorts, and Genomics of Drug Sensitivity in Cancer (GDSC) were utilized to predict the therapeutic response of DLBCL patients. The impact of the hub gene STAT4 on tumor biological behavior and DNA methylation was experimentally validated or accessed by the TSIDE database. The LAR scoring model was developed based on 20 prognosis-related lactate genes, which enabled the division of DLBCL patients into high- and low-risk groups based on the median LAR score. Patients with high-risk DLBCL exhibited significantly worse survival outcomes in both the training cohorts (GSE181063) and the validation cohorts (GSE10846, GSE32918, and GSE69053), as indicated by statistically significant differences (all P<0.05) and area under the curve (AUC) values exceeding 0.6. Immune analyses revealed that low-risk DLBCL patients had higher levels of immune cell infiltration and antitumor immune activation compared to high-risk DLBCL patients. Furthermore, DLBCL patients with high LAR scores were associated with a lower TIDE value and poor therapeutic efficacy of the R-CHOP regimen. GDSC analysis identified 18 drugs that exhibited significant response sensitivity in low-risk DLBCL patients. Moreover, in vitro experiments demonstrated that overexpression of the lactate key gene STAT4 could suppress proliferation and migration, induce cell cycle arrest, and promote cell apoptosis in DLBCL cells. Transcriptional expression and methylation of the STAT4 gene were found to be associated with immunomodulators and chemokines. The lactate-based gene signature effectively predicts the prognosis and regulates TME in DLBCL. Our study underscores the role of lactate gene, STAT4, as an important tumor suppressor in DLBCL. Modulating STAT4 could be a promising strategy for DLBCL in clinical practice.

COL5A2 is a prognostic-related biomarker and correlated with immune infiltrates in gastric cancer based on transcriptomics and single-cell RNA sequencing

BackgroundThere is still a therapeutic challenge in treating gastric cancer (GC) due to its high incidence and poor prognosis. Collagen type V alpha 2 (COL5A2) is increased in various cancers, yet it remains unclear how it contributes to the prognosis and immunity of GC.MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to download transcriptome profiling (TCGA-STAD; GSE84437), single-cell RNA sequencing (scRNA-seq) data (GSE167297) and clinical information. COL5A2 expression and its relationship with clinicopathological factors were analyzed. We conducted survival analysis and Cox regression analysis to evaluate the prognosis and independent factors of GC. Co-expressed analysis was also performed. To identify the underlying mechanism, we conducted analyses of differentially expressed genes (DEGs) and functional enrichment. The correlations between COL5A2 expression and immune cell infiltration levels and immune infiltrate gene marker sets were further explored. Additionally, we analyzed the association of COL5A2 expression with immunological checkpoint molecules. Furthermore, the relationship between COL5A2 expression and immunotherapy sensitivity was also investigated.ResultsCOL5A2 expression was elevated in GC. More than this, the scRNA-seq analysis revealed that COL5A2 expression had a spatial gradient. The upregulated COL5A2 was associated with worse overall survival. A significant correlation was found between COL5A2 overexpression and age, T classification and clinical stage in GC. COL5A2 was found to be an independent factor for the unfortunate outcome in Cox regression analysis. The co-expressed genes of COL5A2 were associated with tumor stage or poor survival. Enrichment analysis revealed that the DEGs were mainly associated with extracellular matrix (ECM)-related processes, PI3K-AKT signaling pathway, and focal adhesion. GSEA analyses revealed that COL5A2 was associated with tumor progression-related pathways. Meanwhile, COL5A2 expression was correlated with tumor-infiltrating immune cells. Moreover, immunophenoscore (IPS) analysis and PRJEB25780 cohorts showed that patients with low COL5A2 expression were highly sensitive to immunotherapy.ConclusionsCOL5A2 might act as a prognostic biomarker of GC prognosis and immune infiltration and may provide a therapeutic intervention strategy.

Abstract PO-025: The effect of tissue of origin on oncogenesis in HPV-related malignancies: Comparative analysis of molecular and immune signatures in HPV-positive head and neck cancer and cervical cancer

Abstract Background: Despite sharing a common causal agent and viral oncogenes, HPV-positive head and neck cancer (HPV+ HNC) and cervical cancer (HPV+ CC) have markedly distinct natural histories and therapy responses. Here we sought to elucidate how the tissue of origin and oncogenic etiology drive molecular and microenvironmental differences between these two malignancies. Methods: Somatic mutation and RNA expression data for HPV+ HNC, HPV+ CC and HPV-negative head and neck cancer (HPV- HNC) were obtained from The Cancer Genome Atlas (TCGA). Mutation data were used to define repertoires of somatic mutations and mutational signatures. Single-sample gene set enrichment analysis (ssGSEA) was used to identify enriched immune signatures. Immune cell infiltration levels were estimated using xCell. Comparisons were primarily made between HPV+ HNC and HPV+ CC samples, with comparisons between HPV+ HNC vs. HPV- HNC tumors serving as a control to distinguish molecular/immune signatures driven by tissue of origin versus viral etiology. Results: Exome and RNA-sequencing data were available for 72 HPV+ HNC, 139 HPV+ CC, and 415 HPV- HNC tumors, and 70 HPV+ HNC, 139 HPV+ CC, and 413 HPV- HNC cases, respectively. Recurrently altered genes in head and neck and cervical cancer were not statistically significantly different between HPV+ HNC and HPV+ CC, although as previously reported HPV+ HNC and HPV- HNC differed by the higher frequency of TP53, CDKN2A, FAT1, and NOTCH1 mutations in the later. An evaluation of mutational signatures revealed that although both HPV+ HNC and CC had evidence of APOBEC mutagenesis (Signatures 2 and 13), Signature 2 and 13 exposures were both significantly higher in HPV+ CC relative to HPV+ HNC. APOBEC enrichment scores confirmed that HPV+ CC had higher APOBEC signal than HPV+ HNC despite both being virally driven. While both cancers were commonly affected by mutagenesis from aging and showed no differences in Signature 1, HPV+ HNC exhibited a higher correlation with Signature 5. Immune de-convolution evaluating 36 cell populations identified 13 cell types with different frequencies between two cancers (q &amp;lt; 0.1). The abundance of B-cell lineages, CD4+ naïve T-cells, and Tregs significantly differed in HPV+ HNC and HPV+ CC (p&amp;lt;0.001). These findings led us to investigate expression signatures of tertiary lymphoid structures, which we identified as markedly higher in HPV+ HNC versus HPV+ CC or HPV- HNC (p &amp;lt; 0.001, for both comparisons). Activated T-cells, however, did not appear to differ between HPV+ HNC or CC as determined by the previously defined cytolytic score. Conclusion: We find that while tissue of origin seems not to influence recurrently mutated oncogenes in HPV-related malignancies, it has significant effects on phenotypic consequences in these tumors including influencing both mutational signature exposure and the tumor microenvironment. These findings may inform further investigations into the unique molecular and microenvironmental characteristics of these virally driven tumors. Citation Format: Reith R. Sarkar, Xin Pei, Andrea Gazzo, Yingjie Zhu, Nancy Lee, Jorge Reis-Filho, Dmitriy Zamarin, Britta Weigelt, Nadeem Riaz. The effect of tissue of origin on oncogenesis in HPV-related malignancies: Comparative analysis of molecular and immune signatures in HPV-positive head and neck cancer and cervical cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-025.

Prognostic significance and immune characteristics of GPR27 in gastric cancer.

Gastric cancer (GC) is one of the most typical cancerous neoplasms occurring in the digestive system. For advanced GC, immunotherapy is the final option for them to prolong survival time. Hence, we aimed to identify new molecular targets to enhance the immunotherapy response in GC individuals. Then we applied bioinformatic analysis to explore the expression profiles of G-protein-coupled receptor 27 (GPR27) transcription and GPR27 methylation. The associations between survival of GC patients and GPR27 transcription and methylation were then analyzed. We also studied the link between GPR27 expression and levels of immune cell infiltration. Finally, we gained insights into the prognostic role of GPR27 protein in 97 cases of GC individuals. According to datasets gained from TCGA, GPR27 mRNA is expressed lower in GC tissues. Down-regulation of GPR27 transcription was related with better survival in GC individuals, and GPR27 cg03024619 had the most significant prognostic value (HR=0.553, P<0.0001). In addition, the expression level of GPR27 has a clear interaction with immune cells' infiltration and their markers. Single-cell analysis displayed that GPR27 is mainly expressed in macrophages. Finally, down-regulation of GPR27 protein was observed in GC tissues and correlated with better survival outcomes. GPR27 can serve as an important prognostic biomarker and exert an immunomodulatory role in GC. Our findings highlight the significance of GPR27 in a variety of cancers, including GC, and provide clues for a better understanding of GPR27 from bioinformatics and clinically validated perspective.

Identification of the ferroptosis regulator HELLS with prognostic value for adrenocortical carcinoma based on integrated analysis and experimental validation.

For adrenocortical carcinoma (ACC), a rare endocrine malignancy with a high rate of mortality and recurrence, it is difficult for clinicians to predict overall survival and select the most effective treatment. Targeting ferroptosis, a form of cell death, has been reported to be a promising therapeutic strategy for ACC; however, the core ferroptosis regulator and its prognostic value in ACC remain unknown. RNA sequencing data and clinical information were downloaded from public databases. Differentially expressed gene and survival analyses were performed to identify candidate ferroptosis regulators. A multivariate Cox regression model was used to construct a gene signature, and a nomogram was constructed to predict the overall survival of patients with ACC. Gene set variation analysis (GSVA) was used to identify underlying aberrant pathways and the relative immune cell infiltration levels of each ACC sample. Immunohistochemistry staining was performed in formalin-fixed paraffin-embedded tumor tissue sections. Ultimately, 23 differentially expressed ferroptosis regulators were identified between normal adrenal gland and ACC tissues, and 50 ferroptosis regulators were related to prognosis, with 13 ferroptosis regulators being simultaneously found to satisfy the differential expression and prognostic value. According to the multivariate Cox regression model, a ferroptosis regulator signature was constructed from 3 genes in The Cancer Genome Atlas (TCGA; hazard ratio =9.01; P=1.39×10-10), and the area under the curve (AUC) values of 3-, 5-, 8-year overall survival were 0.924, 0.906, and 0.866, respectively. The survival analysis and the receiver operating characteristic (ROC) analysis validated the prognostic value of the ferroptosis regulator signature in 3 validation datasets. Moreover, metabolism-, E2F-, MYC-, and G2/M checkpoint-related pathways and aberrant immune cell infiltration levels were identified as being responsible for the different prognosis of risk groups in ACC. HELLS was found to be a significantly differentially expressed ferroptosis-suppressor gene with a prognostic value in ACC and to be highly associated with immune cell infiltration levels and multiple biological functions. A ferroptosis regulator signature showed promising power for predicting the prognosis of ACC, and HELLS was identified as a hub ferroptosis regulator in the initiation and progression of ACC.