Immune Infiltration In Tumor Microenvironment Research Articles

Highly expressed of BID indicates poor prognosis and mediates different tumor microenvironment characteristics in clear cell renal cell carcinoma

BackgroundStudies have found that BH3 interacting domain death agonist (BID) is closely related to the occurrence and development of many kinds of tumors. However, little attention has been paid to the situation of BID in clear cell renal cell carcinoma (ccRCC). So, our aim was to explore the effect of BID in ccRCC.MethodsSurvival analysis, ROC curve, correlation analysis and Cox regression analysis were executed to analyze the prognostic value and clinical correlation of BID in ccRCC. The risk prognosis model was constructed in the training cohort and further validated in the internal testing cohort, ICGC cohort, and GEO cohort. Transcriptome sequencing and immunohistochemical staining of clinical specimens were used to validate the results of bioinformatics analysis. The GSEA, ESTIMATE algorithm, CIBERSORT algorithm, ssGSEA, TIDE score, correlation and difference analysis were used to analyze the effects of BID on immune infiltration in tumor microenvironment (TME).ResultsBID was highly expressed in ccRCC tissues, which was verified by transcriptome sequencing and immunohistochemical staining of clinical specimens. Patients with high expression of BID had a worse prognosis. BID is an independent prognostic factor for ccRCC. The prognostic model based on BID can accurately predict the prognosis of patients in different cohorts. In addition, the expression levels of BID was closely related to immunomodulatory molecules such as PD-1, LAG3, and CTLA4. Enrichment analysis indicated that BID was significantly enriched in immune-related responses and cancer-related pathways. The change of BID expression mediates different characteristics of immune infiltration in TME.ConclusionsBID is highly expressed in ccRCC, which is a reliable biomarker of ccRCC prognosis. It is closely related to TME, and may be a potential target for immunotherapy in patients with ccRCC.

Abstract 6428: Transcriptome analysis of tissues and peripheral blood revealed potential biomarkers for chemo/radio-immunotherapy in non-small cell lung cancer

Abstract Background: Combination of anti-PD-(L)1 antibody with chemotherapy has shown promising efficacy in advanced/metastatic non-small cell lung cancer (NSCLC). Dynamics of peripheral blood mononuclear cells (PBMC) might have impact on repertore of immune cells further resulting different immune infiltration in tumor microenvironment. Thus, monitoring changes in PBMC during therapy or measuring tumor microenvironment provides the possibility to predict the efficacy of tumor immunotherapy. Methods: Patients diagnosed with NSCLC (Stage III-IV)were enrolled in this study. Anti-PD-L1 and chemo/radio combination therapy was performed as adjuvant therapy. Tumor samples were obtained prior to adjuvant therapy PBMC samples were obtaind at multiple time points, including prior adjuvant therapy, 3 months after adjuvant therapy, and 3 months after adjuvant therapy. Tumor and PBMC mRNA sequencing were performed by Amoy Diagnostics Co Ltd. (Xiamen, China). Patients who achieved CR/PR/SD and PFS > 6 months were defined as well responders. Pathway enrichment and GSEA analyses were performed by clusterProfiler (version 4.0.5) on GO, KEGG, and from six different gene sets. Correlations between immune cellular signature ES scores and gene expression were estimated using Pearson correlation. Results: 28 patients were enrolled; mean age was 60.38±7.86 years, 27 (96.4%) patients were male. 21 (75.0%) patients were identified as responder and 7 (25.0%) were non-responder. In the baseline tumor samples, immune infiltration was more extensive in responders compared to non-responders. Cytotoxic lymphocytes, activated CD8+ T cell, and NK cells were significantly enriched in responders. High expression of CCL17 and down regulation of CTSG/PLK1/PRTN3, a signaling axis that inhibits histone H3 hydrolysis and promotes monocyte to macrophage differentiation, was significant in responders. Dynamic monitoring of PBMC before and after treatment showed significant upregulation of immune infiltration-related pathways in responders, including effector cells, NK cells and CD8+ T cells. In the non-responder group, the up-regulated pathways after treatment were mainly enriched in tumor growth rate, EMT, and matrix remodeling. Multi-time point analysis showed that CEACAM5/MKI67 level and tumor proliferation rate in non-responders were higher than those in responders at each time point after treatment. Conclusion: Baseline tumor transcripton signatures and dynamic changes in PBMC could be applied to develop novel biomarkers for immune-related therapy. Patients with stronger immune infiltration signals in baseline tumor samples and PBMC after treatment had better immune response. The upregulation of proliferation-related signals in PBMC predicts poor immune response. Citation Format: Jing Hu, Jianguo Zhang, Peng Cheng, Yanhua Chen, Changbin Zhu, Feilin Yi, Conghua Xie. Transcriptome analysis of tissues and peripheral blood revealed potential biomarkers for chemo/radio-immunotherapy in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6428.

β3GNT9 as a prognostic biomarker in glioblastoma and its association with glioblastoma immune infiltration, migration and invasion.

Studies have shown that the immune infiltration of tumor microenvironment is related to the prognosis of glioblastoma, which is characterized by high heterogeneity, high recurrence rate and low survival rate. To unravel the role of β1,3-N-acetylglucosaminyltransferase-9 (β3GNT9) in the progression of glioblastoma, this study identifies the value of β3GNT9 as a prognostic biomarker in glioblastoma, and investigates the relationship between β3GNT9 expression and glioblastoma immune infiltration, migration and invasion. β3GNT9 expression in glioblastoma was analyzed using the GEPIA database. The clinical features of glioblastoma were screened out from the TCGA database. The relationship between β3GNT9 expression and clinical features was analyzed. The relationship between β3GNT9 and the prognosis of glioblastoma was evaluated through univariate and multivariate COX regression analyses, and the survival analysis was conducted using the Kaplan-Meier method. GSEA was employed to predict the signaling pathway of β3GNT9 in glioblastoma. The correlation between β3GNT9 and tumor immune infiltration was analyzed using the related modules of CIBERSORT and TIMER. A172, U87MG and U251 cell lines were selected to verify β3GNT9 expression in vitro. The effects of β3GNT9 on the migration and invasion of glioblastoma were investigated through cell scratch and invasion assays. β3GNT9 expression in glioblastoma group was significantly higher than that in normal brain tissue group (P<0.05). The overall survival rate in high β3GNT9 expression group was significantly lower than that in low β3GNT9 expression group (P<0.05). Regression analyses suggested that β3GNT9, involved primarily in glucosamine degradation and extracellular matrix receptor interaction, could be an independent prognostic factor for glioblastoma. CIBERSORT and GEPIA database analyses showed that β3GNT9 was correlated with tumor infiltrating immune cells such as T follicular helper cells, activating natural killer cells, monocytes, macrophages, and eosinophils, thus affecting the immune microenvironment of glioblastoma. Cell experiments confirmed that β3GNT9 was highly expressed in A172, U87MG and U251 cell lines (P<0.05), and promoted the migration and invasion of glioblastoma (P<0.05). The increased expression of β3GNT9 in glioblastoma can affect the immune microenvironment of glioblastoma and promote its migration and invasion. β3GNT9 can be used as a potential independent prognostic biomarker for patients with glioblastoma.

A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma.

Accumulating evidence has suggested that glycometabolism plays an important role in the pathogenesis of tumorigenesis. However, few studies have investigated the prognostic values of glycometabolic genes in patients with osteosarcoma (OS). This study aimed to recognize and establish a glycometabolic gene signature to forecast the prognosis, and provide therapeutic options for patients with OS. Univariate and multivariate Cox regression, LASSO Cox regression, overall survival analysis, receiver operating characteristic curve, and nomogram were adopted to develop the glycometabolic gene signature, and further evaluate the prognostic values of this signature. Functional analyses including Gene Ontology (GO), kyoto encyclopedia of genes and genomes analyses (KEGG), gene set enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), and competing endogenous RNA (ceRNA) network, were used to explore the molecular mechanisms of OS and the correlation between immune infiltration and gene signature. Moreover, these prognostic genes were further validated by immunohistochemical staining. A total of four genes including PRKACB, SEPHS2, GPX7, and PFKFB3 were identified for constructing a glycometabolic gene signature which had a favorable performance in predicting the prognosis of patients with OS. Univariate and multivariate Cox regression analyses revealed that the risk score was an independent prognostic factor. Functional analyses indicated that multiple immune associated biological processes and pathways were enriched in the low-risk group, while 26 immunocytes were down-regulated in the high-risk group. The patients in high-risk group showed elevated sensitivity to doxorubicin. Furthermore, these prognostic genes could directly or indirectly interact with other 50 genes. A ceRNA regulatory network based on these prognostic genes was also constructed. The results of immunohistochemical staining showed that SEPHS2, GPX7, and PFKFB3 were differentially expressed between OS tissues and adjacent normal tissues. The preset study constructed and validated a novel glycometabolic gene signature which could predict the prognosis of patients with OS, identify the degree of immune infiltration in tumor microenvironment, and provide guidance for the selection of chemotherapeutic drugs. These findings may shed new light on the investigation of molecular mechanisms and comprehensive treatments for OS.

Pan-cancer analysis of SYNGR2 with a focus on clinical implications and immune landscape in liver hepatocellular carcinoma

BackgroundSynaptogyrin-2 (SYNGR2), as a member of synaptogyrin gene family, is overexpressed in several types of cancer. However, the role of SYNGR2 in pan-cancer is largely unexplored.MethodsFrom the TCGA and GEO databases, we obtained bulk transcriptomes, and clinical information. We examined the expression patterns, prognostic values, and diagnostic value of SYNGR2 in pan-cancer, and investigated the relationship of SYNGR2 expression with tumor mutation burden (TMB), microsatellite instability (MSI), immune infiltration, and immune checkpoint (ICP) genes. The gene set enrichment analysis (GSEA) software was used to perform pathway analysis. Besides, we built a nomogram of liver hepatocellular carcinoma patients (LIHC) and validated its prediction accuracy.ResultsSYNGR2 was highly expressed in most cancers. The high expression of SYNGR2 significantly reduced the overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in multiple types of cancer. Also, receiver operating characteristic (ROC) curve analysis demonstrated that SYNGR2 showed high accuracy in distinguishing cancerous tissues from normal ones. Moreover, SYNGR2 expression was correlated with TMB, MSI, immune scores, and immune cell infiltrations. We also analyzed the association of SYNGR2 with immunotherapy response in LIHC. Finally, a nomogram including SYNGR2 and pathologic T, N, M stage was built and exhibited good predictive power for the OS, DSS, and PFI of LIHC patients.ConclusionOverall, SYNGR2 is a critical oncogene in various tumors. SYNGR2 participates in the carcinogenic progression, and may contribute to the immune infiltration in tumor microenvironment. Our study suggests that SYNGR2 can serve as a predictor related to prognosis in pan-cancer, especially LIHC.

SAA1 Has Potential as a Prognostic Biomarker Correlated with Cell Proliferation, Migration, and an Indicator for Immune Infiltration of Tumor Microenvironment in Clear Cell Renal Cell Carcinoma.

The tumor microenvironment (TME) plays an important part in the initiation and development of clear cell renal cell carcinoma (ccRCC). However, an understanding of the immune infiltration in TME is still unknown. Our study aims to explore the correlation between the TME and the clinical features, as well as the prognosis of ccRCC. In the present study, ESTIMATE and CIBERSORT computational methods were applied to calculate the proportion of tumor-infiltrating immune cells (TICs) and the amount of immune and stromal fractions in the ccRCC form The Cancer Genome Atlas (TCGA) database. Then, we sought to find out those immune cell types and genes which may play a significant role and validated them in the GEO database. Furthermore, an immunohistochemical analysis of our external validation dataset was used to detect SAA1 and PDL1 expression in the ccRCC cancer tissues and corresponding normal tissues. Statistical analysis was performed to study the relationship between SAA1 and clinical characteristics, as well as PDL1 expression. Furthermore, a ccRCC cell model with SAA1 knockdown was constructed, which was used for cell proliferation and the migration test. The intersection analysis of the univariate COX and PPI analysis were performed to imply Serum Amyloid A1 (SAA1) as a predictive factor. The expression of SAA1 was significantly negatively correlated to OS and positively correlated to the clinical TMN stage system. The genes in the high-expression SAA1 group were basically enriched in immune-related activities. The proportion of mast cells resting was negatively correlated with SAA1 expression, indicating that SAA1 may be involved in the maintenance of the immune status for the TME. Moreover, the PDL1 expression was positively related to the SAA1 expression and negatively correlated with the patients' prognosis. Further experiments revealed that the knockdown of SAA1 inhibited ccRCC development through suppressing cell proliferation and migration. SAA1 may be a novel marker for the prognosis prediction of ccRCC patients and may play a vital role in the TME by mast cell resting and PDL1 expression. SAA1 has the potential to become a therapeutic target and indicator for immune target therapy in ccRCC treatment.

Trial in progress: Phase II study of niraparib and dostarlimab for the treatment of germline or somatic homologous recombination repair mutated metastatic pancreatic cancer.

TPS780 Background: Pancreatic adenocarcinoma is an aggressive malignancy with a limited number of therapeutic options. One subset of patients (up to 15%) carries germline and/or somatic mutations in homologous recombination repair genes, most notably BRCA1, BRCA2 and PALB2 amongst others, that confer sensitivity to PARP inhibition. Combinations of PARP inhibitors with anti-PD1 immunotherapy have shown activity in breast and ovarian cancer and have not yet been thoroughly studied in pancreatic cancer. Methods: We designed a single-arm phase 2 investigator-initiated study utilizing the combination of niraparib, a highly selective PARP inhibitor and a dostarlimab, an anti PD1 antibody, in the subset of pancreatic cancer patients with germline or somatic mutations in BRCA1/2, PALB2, BARD1, RAD51C, or RAD51D. Additional inclusion criteria include metastatic pancreatic adenocarcinoma, receipt of a platinum agent in 1st or 2nd line unless contraindicated, and at least 1 but not more than 2 prior lines of systemic therapy not including maintenance. Prior PARP inhibition is allowed, but not immediately prior to enrollment. Exclusion criteria include active unstable autoimmune disease or prior malignancy requiring active treatment within 2 years. Patients are treated with niraparib 200 mg orally once daily on days 1 through 21 of a 21 day cycle. Dostarlimab is administered IV 500 mg every 3 weeks for the 1st 4 cycles and then 1000 mg IV every 6 weeks subsequently. The primary endpoint of the study is the disease control rate at 12 weeks using standard iRECIST criteria. Twenty patients will be enrolled to ensure 19 evaluable. The design has 80% power to detected improvement in disease control rate from 25-50% with significance level of 0.10. Descriptive factors include gene mutated for inclusion, germline/somatic, and platinum refractoriness. Given the size of the study along with genetic heterogeneity there will be no interim analysis. Patients are being enrolled at 3 Mayo clinic sites in Rochester Minnesota, Phoenix Arizona, Jacksonville Florida. To date, 13 patients have been enrolled across all 3 sites. Full accrual is anticipated by early 2023. Correlative studies include genomic characterization of baseline tumors, assessment of immune infiltration of tumor microenvironment, tumor collection for organoid/xenograft, and serial circulating cell-free DNA and immune biomarkers. Trial Identifiers: NCT04493060, Mayo: MC1841. Supported by Glaxo Smith Kline. Clinical trial information: NCT04493060 .

A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer.

Currently, predictive models were not developed based on the signaling pathway signatures of immune-related lncRNAs in breast cancer (BRCA) patients. We selected unsupervised hierarchical clustering algorithm to classify patients with BRCA based on the significant immune-derived lncRNAs from the TCGA dataset. And different methods including ESTIMATE, ImmuneCellAI, and CIBERSORT were performed to evaluate the immune infiltration of tumor microenvironment. Using Lasso regression algorithm, we filtered the significant signaling pathways enriched by GSEA, GSVA, or PPI analysis to develop a prognostic model. And a nomogram integrated with clinical factors and significant pathways was constructed to predict the precise probability of overall survival (OS) of BRCA patients in the TCGA dataset (n = 1,098) and another two testing sets (n = 415). BRCA patients were stratified into the PC (n = 571) and GC (n = 527) subgroup with significantly different prognosis with 550 immune-related lncRNAs in the TCGA dataset. Integrated analysis revealed different immune response, oncogenic signaling, and metabolic reprograming pathways between these two subgroups. And a 5-pathway signature could predict the prognosis of BRCA patients between these two subgroups independently in the TCGA dataset, which was confirmed in another two cohorts from the GEO dataset. In the TCGA dataset, 5-year OS rate was 78% (95% CI: 73-84) vs. 82% (95% CI: 77-87) for the PC and GC group (HR = 1.63 (95% CI: 1.17-2.28), p = 0.004). The predictive power was similar in another two testing sets (HR > 1.20, p < 0.01). Finally, a nomogram is developed for clinical application, which integrated this signature and age to accurately predict the survival probability in BRCA patients. This 5-pathway signature correlated with immune-derived lncRNAs was able to precisely predict the prognosis for patients with BRCA and provided a rich source characterizing immune-related lncRNAs and further informed strategies to target BRCA vulnerabilities.

Identification of molecular subtypes based on liquid-liquid phase separation and cross-talk with immunological phenotype in bladder cancer.

Mounting evidence has demonstrated that an imbalance in liquid-liquid phase separation (LLPS) can induce alteration in the spatiotemporal coordination of biomolecular condensates, which plays a role in carcinogenesis and cachexia. However, the role of LLPS in the occurrence and progression of bladder cancer (BLCA) remains to be elucidated. Identifying the role of LLPS in carcinogenesis may aid in cancer therapeutics. A total of 1,351 BLCA samples from six cohorts were retrieved from publicly available databases like The Cancer Genome Atlas, Gene Expression Omnibus, and ArrayExpress. The samples were divided into three distinct clusters, and their multi-dimensional heterogeneities were explored. The LLPS patterns of all patients were determined based on the LLPS-related risk score (LLPSRS), and its multifaceted landscape was depicted and experimentally validated at the multi-omics level. Finally, a cytotoxicity-related and LLPSRS-based classifier was established to predict the patient's response to immune checkpoint blockade (ICB) treatment. Three LLPS-related subtypes were identified and validated. The differences in prognosis, tumor microenvironment (TME) features, cancer hallmarks, and certain signatures of the three LLPS-related subtypes were validated. LLPSRS was calculated, which could be used as a prognostic biomarker. A close correlation was observed between clinicopathological features, genomic variations, biological mechanisms, immune infiltration in TME, chemosensitivity, and LLPSRS. Furthermore, our classifier could effectively predict immunotherapy response in patients with BLCA. Our study identified a novel categorization of BLCA patients based on LLPS. The LLPSRS could predict the prognosis of patients and aid in designing personalized medicine. Further, our binary classifier could effectively predict patients' sensitivity to immunotherapy.

Pyroptosis related genes signature predicts prognosis and immune infiltration of tumor microenvironment in hepatocellular carcinoma

Little is known on the relationship between the expression of pyroptosis related genes (PRGs) and prognosis of hepatocellular carcinoma (HCC). In this study, a specific PRGs prognostic model was developed with an aim to improve therapeutic efficiency among HCC patients. In total, 42 PRGs that were differentially expressed between HCC tissues and adjacent tissues and we exhibited the mutation frequency, classification, the location of copy number variation (CNV) alteration and the CNV variation frequency of PRGs. Two clusters were distinguished by the consensus clustering analysis based on the 42 differentially expressed genes (DEGs). There were significant differences in clinical features including T stage, grade, gender, and stage among different clusters. Kaplan–Meier curve analysis showed that cluster 1 had a better prognosis than cluster 2. The prognostic value of PRGs for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Based on the univariate analysis and multivariate analysis, a 10-gene signature was built and all HCC patients in the TCGA cohort were divided into low-risk group and high-risk group. HCC patients in the high-risk group showed significantly lower survival possibilities than those in the low-risk group (P < 0.001). Utilizing the median risk score from the TCGA cohort, HCC patients from International Cancer Genome Consortium (ICGC)-LIRI-JP cohort and Gene Expression Omnibus (GEO) cohort (GSE14520) were divided into two risk subgroups. The result showed that overall survival (OS) time was decreased in the high-risk group. Combined with the clinical characteristics, the risk score was an independent factor for predicting the OS of HCC patients. Then, ROC curve and survival analysis were performed to evaluate the prognostic prediction value of the model. Finally, we constructed a PRGs clinical characteristics nomogram to further predict HCC patient survival probability. There were significant differences in immune cell infiltration, GSEA enrichment pathway, IC50 of chemotherapeutics, PRGs mutation frequency between high-risk group and low-risk group. This work suggests PRGs signature played a crucial role in predicting the prognosis, infiltration of cancer microenvironment, and sensitivity of chemotherapeutic agents.

PD-1 blockage combined with vaccine therapy can facilitate immune infiltration in tumor microenvironment of Lynch syndrome colon cancer.

Background: Lynch syndrome is a genetic disease resulting from mismatch repair gene mutation. Vaccine therapy can enhance the immunogenicity of Lynch syndrome and improve the therapeutic efficacy of immunotherapy. However, there is no approved Lynch syndrome vaccine coming onto the market. Methods: Herein, we used gene knockdown method to construct Lynch syndrome cell model, paving way for us to develop Lynch syndrome tumor lysate vaccine. Then the isograft technique was employed for constructing the tumor-bearing mouse model of Lynch syndrome. And this isograft model was treated with PD-1 monoclonal antibody and tumor vaccine, respectively. Flow cytometry was used for detecting the proportion of immune cells and immunosuppressive cells, and ELISA was used for detecting the contents of chemokines and cytokines in the blood circulation system and tumor tissues of mice. Finally, IHC was used to detect the effects of tumor vaccines as well as PD-1 antibody on tumor tissue proliferation and angiogenesis. Results: The results demonstrated that tumor vaccine could prolong the overall survival of mice, and improve the disease-free survival rate of mice. The vaccine could increase the proportion of inflammatory cells and decrease the proportion of anti-inflammatory cells in the blood circulation system of mice. In addition, tumor vaccine could also improve inflammatory infiltration in the tumor microenvironment and reduce the proportion of immunosuppressive cells. The results of IHC showed that tumor vaccine could inhibit angiogenesis and tumor cell proliferation in mouse tumor tissues. Conclusion: In colon cancer associated with Lynch syndrome, tumor vaccine can hinder the growth of tumor cells, and assist immunotherapy whose therapeutic effect on this kind of cancer is thus enhanced.

Crosstalk of three novel types of programmed cell death defines distinct microenvironment characterization and pharmacogenomic landscape in breast cancer.

BackgroundPrior studies have highlighted that novel programmed cell death (PCD) modalities, including ferroptosis, pyroptosis, and necroptosis, are correlated with tumor progression and antitumor immunity. Nonetheless, comprehensive analysis of tumor microenvironment (TME) profiles mediated by the crosstalk of distinct PCD forms has not been conducted in breast cancer (BC).MethodsHere, we curated 34 identified PCD-associated genes (PCDAGs) and applied the consensus clustering algorithm to establish PCD-mediated tumor patterns in BC. Subsequently, based on prognostic differentially expressed genes extracted from distinct PCD-mediated patterns, we applied the LASSO algorithm to construct CD_Score. Furthermore, the correlation analysis between CD_Score and TME features, molecular subtypes, clinicopathological characteristics, drug response, and immunotherapeutic efficacy was performed.ResultsThree distinct PCD-clusters were determined among 2,038 BC samples, which did not only display different clinical outcomes but highly correlated to the established immunological tumor phenotypes: “desert,” “excluded,” and “inflamed” immune profiles. Based on the CD_Score derived from the PCD-related gene signature, BC patients could be stratified into CD_Score-low and -high group, of which the former displayed satisfactory survival outcome and enhanced immune infiltration. Further exploration identified that the CD_Score-high group significantly correlated with elevated neoantigen load and higher mutation frequency in SMGs (e.g., TP53 and MAP3K1) and reduced expression of immune checkpoint proteins.ConclusionsThis research is the first to emphasize the close relationship between distinct cell death modalities and the diversity and complexity of immune infiltration in TME. We established the CD_Score, which could help enhance our cognition of TME features and facilitate the clinical application of immunotherapy.

MCEMP1 is a potential therapeutic biomarker associated with immune infiltration in advanced gastric cancer microenvironment

BackgroundOver the last decade, breakthroughs have been made in cancer immunotherapy. However, for advanced gastric cancer (AGC), the complexity and heterogeneity of the tumor microenvironment (TME) has been the biggest challenge for immunotherapy. Therefore, an intensive study on TME of AGC is necessary. MethodsESTIMATE and CIBERSORT algorithms were applied to analyze the transcriptome data of AGC using TCGA database systematically. We identified mast cell-expressed membrane protein 1 (MCEMP1) as a potential prognostic marker by protein–protein interaction (PPI) and Univariate Cox regression. The expression of MCEMP1 was evaluated by immunohistochemistry (IHC) and quantitative real time PCR. We assessed prognostic values of MCEMP1 with use of Kaplan-Meier and Multivariate Cox regression analysis. Gene set enrichment analysis (GSEA) was used to analyze the molecular mechanism of MCEMP1. The correlation between MCEMP1 expression and tumor immune infiltration was analyzed by the TIMER database and CIBERSORT algorithm, which was confirmed by IHC. ResultsThe mRNA and protein expression of MCEMP1 was up-regulated substantially and related to poor survival in AGC. GSEA analysis revealed that MCEMP1 was involved in the immune-related signaling pathways. We further demonstrated that the expression of MCEMP1 was correlated with multiple immune cells and immune checkpoints. The results of IHC indicated that there was a positive correlation between PD-L1 expression and MCEMP1, suggesting that MCEMP1 may affect the prognosis of AGC patients by regulating immune infiltration and the function of immune cells. ConclusionMCEMP1 may serve as a biomarker associated with immune infiltration in TME and could be a potential therapeutic target for AGC patients.

PTPRN Serves as a Prognostic Biomarker and Correlated with Immune Infiltrates in Low Grade Glioma.

Background: Glioma is one of the most common malignant tumors of the central nervous system. Immune infiltration of tumor microenvironment was associated with overall survival in low grade glioma (LGG). However, effects of Tyrosine phosphatase receptor type N (PTPRN) on the progress of LGG and its correlation with tumor infiltration are unclear. Methods: Here, datasets of LGG were from The Cancer Genome Atlas (TCGA) and normal samples were from GTEx dataset. Gepia website and Human Protein Atlas (HPA) Database were used to analyze the mRNA and protein expression of PTPRN. We evaluated the influence of PTPRN on survival of LGG patients. MethSurv was used to explore the expression and prognostic patterns of single CpG methylation of PTPRN gene in LGG. The correlations between the clinical information and PTPRN expression were analyzed using logistic regression and Multivariate Cox regression. We also explored the correlation between PTPRN expression and cancer immune infiltration by TIMER. Gene set enrichment analysis (GSEA) was formed using TCGA RNA-seq datasets. Results: PTPRN mRNA and protein expression decreased in LGG compared to normal brain tissue in TCGA and HPA database. Kaplan-Meier analysis showed that the high expression level of PTPRN correlated with a good overall survival (OS) of patients with LGG. The Multivariate Cox analysis demonstrated that PTPRN expression and other clinical-pathological factors (age, WHO grade, IDH status, and primary therapy outcome) significantly correlated with OS of LGG patients. The DNA methylation pattern of PTPRN with significant prognostic value were confirmed, including cg00672332, cg06971096, cg01382864, cg03970036, cg10140638, cg16166796, cg03545227, and cg25569248. Interestingly, PTPRN expression level significantly negatively correlated with infiltrating level of B cell, CD4+ T cells, Macrophages, Neutrophils, and DCs in LGG. Finally, GSEA showed that signaling pathways, mainly associated with tumor microenvironment and immune cells, were significantly enriched in PTPRN high expression. Conclusion: PTPRN is a potential biomarker and correlates with tumor immune infiltration in LGG.

ERBB3 methylation and immune infiltration in tumor microenvironment of cervical cancer

ERBB3, a member of the ERBB family of receptor tyrosine kinases, plays an important role in cancer, despite its lack of intrinsic carcinogenic mechanism of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Research on bioinformatics methods through multi-omics, this work proves that ERBB3 gene mutation, methylation modification have extensive regulatory mechanisms on the CESC microenvironment. We found that ERBB3 is involved in carcinogenesis of cervical cancer and is not associated with its prognosis. The carcinogenic mechanism is mainly related to the suppression of the immune system between tumor infiltrating lymphocytes (TILs) and the methylation of the RNA level. Our study indicated ERBB3 is more likely to be a carcinogenic factor than a key prognostic factor for cervical cancer. Methylation of ERBB3 may work as a checkpoint immunotherapy target in CESC, DNA methylation modification of the 4480 base pair downstream of ERBB3 transcription initiation site was the highest.

Long Noncoding RNA H19 Derived from M2 Tumor-Associated Macrophages Promotes Bladder Cell Autophagy via Stabilizing ULK1.

Purpose M2-like tumor-associated macrophages (TAMs) are crucial component of immune infiltration in tumor microenvironment (TME), and exosomes derived from TAMs contributed to the regulation of tumor progression through cellular communication. However, in bladder cancer, the role of exosomal components still remains largely unknown. In the current study, we investigated the role of exosomes derived from M2-like TAMs in the regulation of autophagy in bladder cancer (BC) cells. Methods THP-1 cells were stimulated with IL-4 and IL-13 for the polarization of TAMs, and exosomes were extracted by ultracentrifugation. H19 overexpression plasmid and H19 siRNAs were used in the study. Fluorescent analysis was performed for GFP-LC3 detection. Levels of autophagy and potential target were confirmed by western blot assay and immunoprecipitation. Results We found that TAMs-exosome treatment significantly enhanced autophagy in BC cells, and the expression of lncRNA H19 was greatly upregulated in TAMs-exosome. Silencing of lncRNA H19 in TAMs-exo obviously decreased the levels of LC3-II expression whereas the p62 levels were increased. Mechanistically, silencing of exosomal H19 from TAMs alleviated ULK1 stabilization in BC cells through promoting K48-linked polyubiquitination of ULK1. At last, we found that overexpression of exosomal H19 from TAMs suppressed the interaction between ULK1 and its specific E3 ligase NEDD4L in BC cells. Conclusion We revealed the effect of TAMs-exo-contained lncRNA H19 on regulating autophagy of bladder cancer cells, which indicated that targeting TAMs-H19 is a promising therapeutic strategy for the treatment of BC.

Association of ADAP2 gene with prognosis and immune infiltration in tumor microenvironment in patients with lung squamous cell carcinoma

Association of ADAP2 gene with prognosis and immune infiltration in tumor microenvironment in patients with lung squamous cell carcinoma

The Pyroptosis Related Genes Signature Predicts Prognosis and Immune Infiltration of Tumor Microenvironment in Hepatocellular Carcinoma

The Pyroptosis Related Genes Signature Predicts Prognosis and Immune Infiltration of Tumor Microenvironment in Hepatocellular Carcinoma

BCL10 correlates with bad prognosis and immune infiltration of tumor microenvironment in hepatocellular carcinoma.

It has been reported that B-cell CLL-lymphoma 10 (BCL10) serves as an oncogene in cervical cancer. However, the roles of BCL10 in hepatocellular carcinoma (HCC), especially involved in immune infiltration remain not clear. This study aims to explore the relationship between BCL10 and the prognosis and clinical significance, and immune infiltration in HCC. The expression of BCL10 was analyzed between HCC samples and non-tumor samples in the multiple datasets. In addition, the prognostic values of BCL10 and its methylation in HCC were also investigated. The clinical significance of BCL10 has also been explored. Furthermore, the correlation between BCL10 and immune infiltration in HCC microenvironment was assessed. Finally, the biological behaviors of BCL10 in HCC were verified by cell function experiments. It was found that the expression levels of BCL10 were increased in HCC patients in multiple datasets. Moreover, the increased BCL10 and its reduced methylation were associated with the poor survival. BCL10 was significantly associated with immune infiltration. When BCL10 was knocked down in HCC cells, their proliferation ability was significantly inhibited, their migration was significantly decreased, their apoptosis was significantly increased, and AKT signaling pathway was inhibited. In conclusion, BCL10 is a potential prognostic and diagnostic biomarker related to immune infiltration in HCC microenvironment.

M6A Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Pancreatic Cancer.

Recent studies have shown that RNA N6-methyladenosine (m6A) modification plays an important part in tumorigenesis and immune-related biological processes. However, the comprehensive landscape of immune cell infiltration characteristics in the tumor microenvironment (TME) mediated by m6A methylation modification in pancreatic cancer has not yet been elucidated. Based on consensus clustering algorithm, we identified two m6A modification subtypes and then determined two m6A-related gene subtypes among 434 pancreatic cancer samples. The TME characteristics of the identified gene subtypes were highly consistent with the immune-hot phenotype and the immune-cold phenotype respectively. According to the m6A score extracted from the m6A-related signature genes, patients can be divided into high and low m6A score groups. The low score group displayed a better prognosis and relatively strong immune infiltration. Further analysis showed that low m6A score correlated with lower tumor mutation burden and PD-L1 expression, and indicated a better response to immunotherapy. In general, m6A methylation modification is closely related to the diversity and complexity of immune infiltration in TME. Evaluating the m6A modification pattern and immune infiltration characteristics of individual tumors can help deepen our understanding of the tumor microenvironment landscape and promote a more effective clinical practice of immunotherapy.