Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine.
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ABSTRACT:
SUBMITTER: Zheng X
PROVIDER: S-EPMC8645679 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundBladder urothelial carcinoma (BLCA) is associated with high mortality and recurrence. Although mRNA-based vaccines are promising treatment strategies for combating multiple solid cancers, their efficacy against BLCA remains unclear. We aimed to identify potential effective antigens of BLCA for the development of mRNA-based vaccines and screen for immune clusters to select appropriate candidates for vaccination.MethodsGene expression microarray data and clinical information were retrieved from The Cancer Genome Atlas and GSE32894, respectively. The mRNA splicing patterns were obtained from the SpliceSeq portal. The cBioPortal for Cancer Genomics was used to visualize genetic alteration profiles. Furthermore, nonsense-mediated mRNA decay (NMD) analysis, correlation analysis, consensus clustering analysis, immune cell infiltration analysis, and weighted co-expression network analysis were conducted.ResultsSix upregulated and mutated tumor antigens related to NMD, and infiltration of APCs were identified in patients with BLCA, including HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2. The patients were subdivided into two immune clusters (IC1 and IC2) with distinct clinical, cellular and molecular features. Patients in IC1 represented immunologically 'hot' phenotypes, whereas those in IC2 represented immunologically 'cold' phenotypes. Moreover, the survival rate was better in IC2 than in IC1, and the immune landscape of BLCA indicated significant inter-patient heterogeneity. Finally, CALD1, TGFB3, and ANXA6 were identified as key genes of BLCA through WGCNA analysis, and their mRNA expression levels were measured using qRT-PCR.ConclusionHP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2 were identified as potential antigens for developing mRNA-based vaccines against BLCA, and patients in IC2 might benefit more from vaccination.
| S-EPMC9905425 | biostudies-literature
Project description:BackgroundmRNA vaccines are a novel technology that provide a potential strategy for cancer treatment. However, few studies exist that are focused on the application and development of mRNA vaccines in bladder cancer (BLCA). Therefore, this study filtered candidate antigens and specific mRNA-suitable populations in BLCA via comprehensive multi-omics analysis.MethodsClinical information, follow-up information, and gene expression profiles were obtained from the TCGA and GEO databases. Somatic mutation and DNA copy number variation of BLCA were visualized by cBioPortal. Significant survival genes were analyzed by GEPIA2. TIMER was used to evaluate the connection between candidate antigens and infiltration of antigen-presenting cells. Consensus clustering analysis was performed to identify immune subtypes using the ConsensusClusterPlus package. The Monocle package was used to visualize the immune landscapes of each BLCA patient. Weighted gene co-expression network analysis (WGCNA) was used to identify key genes for mRNA vaccines.ResultsAP2S1, P3H4, and RAC3 were identified as candidate tumor-specific antigens for BLCA. Three immune subtypes were classified based on immune-related gene expression profiles. Patients with the BCS2 subtype were characterized as immune "cold" and exhibited upregulation of immunogenic cell death modulators, whereas patients with BCS1 and BCS3 were immune "hot" and had upregulation of immune checkpoints. Interestingly, patients with the BCS2 subtype had a better prognosis than other subtypes. The immune landscapes of each patient were visualized and revealed the heterogeneity within the BCS1 subtype. Finally, 13 key immune genes were identified.ConclusionsAP2S1, P3H4, and RAC3 were identified as candidate tumor-specific antigens, and patients with the BCS2 and BCS1A subtypes were identified as candidate populations for mRNA vaccines. In summary, this study provides novel insights and a theoretical basis for mRNA vaccine development in BLCA and other malignancies.
| S-EPMC9263198 | biostudies-literature
Project description:BackgroundThere are currently no treatments targeting the immune microenvironment (TME) as an extension of immunotherapy. Our research aims to provide guidance for the development of immune-related mRNA vaccines and the identification of immune subtypes for vaccine treatment in lung adenocarcinoma (LUAD).MethodsHTRNA-Seq and single cell RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) and Gene-Expression Omnibus (GEO, GSE87340, GSE140343, GSE148071) databases. Immune checkpoints (ICP) were used as criteria to differentiate immune subtypes and immune resistance score (IRS) system is constructed by ssGSEA to judge the immune microenvironment status of patients.ResultsTwo overexpressed tumor-specific antigens, including ZC3H12D and TXNDC5, were found to be associated with both disease-free survival (DFS) and overall survival (OS). In addition, the expression of two genes correlated with antigen-presenting cell (APC) infiltration and tumor purity. Subsequently, the immune subtype of the patient was defined by constructing an IRS scoring system. The lower the IRS, the stronger the immune response in the TME. This result was verified in external datasets and at the single-cell level.ConclusionsZC3H12D and TXNDC5 are potential tumor-specific antigens for developing mRNA vaccines in LUAD. Importantly, patients with low IRS are more suitable for the use of immunotherapy and vaccines. Our research enhances understanding of TME features and guides more effective immunotherapy strategies.
| S-EPMC9483806 | biostudies-literature
Project description:Recent evidence suggested that the mRNA vaccine has been effective for many tumors, but its progress in gliomas was slow. In this study, we screened potential tumor antigens and suitable populations for mRNA vaccine to develop mRNA vaccine for glioma. We integrated the normalized RNA sequencing expression data and somatic mutation data from TCGA-GBM, TCGA-LGG, and CGGA datasets. Putative antigens in glioma were identified by selecting highly mutated genes with intimate correlation with clinical survival and immune infiltration. An unsupervised partition around medoids algorithm was utilized to stably cluster the patients into five different immune subtypes. Among them, IS1/2 was cold tumor with low tumor mutation burden (TMB), immunogenic cell death (ICDs), and immune checkpoints (ICPs), and IS4/5 was hot tumor with high TMB, ICDs, and ICPs. Monocle3 package was used to evaluate the immune status similarity and evolution in glioma, which identified cluster IS2A/2B within IS2 subtype to be more suitable vaccination receivers. Weighted gene co-expression network analysis identified five hub immune genes as the biomarkers of patients' immune status in glioma. In conclusion, NAT1, FRRS1, GTF2H2C, BRCA2, GRAP, NR5A2, ABCB4, ZNF90, ERCC6L, and ZNF813 are potential antigens suitable for glioma mRNA vaccine. IS1/2A/2B are suitable for mRNA vaccination.
| S-EPMC9249984 | biostudies-literature
Project description:BackgroundmRNA-based cancer vaccines have been considered a promising anticancer therapeutic approach against various cancers, yet their efficacy for malignant mesothelioma (MESO) is still not clear. The present study is designed to identify MESO antigens that have the potential for mRNA vaccine development, and to determine the immune subtypes for the selection of suitable patients.MethodsA total of 87 MESO datasets were used for the retrieval of RNA sequencing and clinical data from The Cancer Genome Atlas (TCGA) databases. The possible antigens were identified by a survival and a genome analysis. The samples were divided into two immune subtypes by the application of a consensus clustering algorithm. The functional annotation was also carried out by using the DAVID program. Furthermore, the characterization of each immune subtype related to the immune microenvironment was integrated by an immunogenomic analysis. A protein-protein interaction network was established to categorize the hub genes.ResultsThe five tumor antigens were identified in MESO. FAM134B, ALDH3A2, SAV1, and RORC were correlated with superior prognoses and the infiltration of antigen-presenting cells (APCs), while FN1 was associated with poor survival and the infiltration of APCs. Two immune subtypes were identified; TM2 exhibited significantly improved survival and was more likely to benefit from vaccination compared with TM1. TM1 was associated with a relatively quiet microenvironment, high tumor mutation burden, and enriched DNA damage repair pathways. The immune checkpoints and immunogenic cell death modulators were also differentially expressed between two subtypes. Finally, FN1 was identified to be the hub gene.ConclusionsFAM134B, ALDH3A2, SAV1, RORC, and FN1 are considered as possible and effective mRNA anti-MESO antigens for the development of an mRNA vaccine, and TM2 patients are the most suitable for vaccination.
| S-EPMC9331978 | biostudies-literature
Project description:Rationale: Diffuse glioma patients have high mortality and recurrence despite multimodal therapies. This study aims to identify the potential tumor antigens for mRNA vaccines and subtypes suitable for the immunotherapy of patients with diffuse glioma. Methods: Gene expression profiles and corresponding clinical information were obtained from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) databases. Genetic alterations were extracted from cBioPortal. Differential gene analysis, survival analysis, correlation analysis, consensus clustering analysis, and immune cell infiltration analysis were conducted based on the various databases. Finally, the hub genes, the modules related to tumor antigens, and the immune subtypes were identified using WGCNA method. Results: Three over-expressed, amplified, and mutated tumor antigens, including KDR, COL1A2, and SAMD9, were associated with clinical outcomes. The expression of the three genes had a positive correlation with the abundance of antigen-presenting cells (APCs) and APC marker expression. Subsequently, three immune subtypes (Ims1, Ims2, and Ims3) were distinguished in the TCGA cohort, which exhibited distinct molecular, cellular, and clinical characteristics consistent with the CGGA cohort. Diffuse gliomas with subtype Ims1 were more malignant with immunosuppressive phenotypes and more associated with poor prognosis than the other two subtypes. The three antigens and the immune checkpoints were differentially expressed among the three immune subtypes. Finally, functional enrichment analysis of the genes related to tumor antigens and immune subtypes suggested that they are enriched in many immune-associated processes. Conclusions: KDR, COL1A2, and SAMD9 are potential antigens for developing mRNA vaccines against diffuse glioma. The results suggest that immunotherapy targeting these three antigens is more suitable for patients with subtype Ims1. This study provides insights into immunotherapy for diffuse glioma.
| S-EPMC8581422 | biostudies-literature
Project description:BackgroundAs an important part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against lower grade glioma (LGG) remains undefined. Immunophenotyping of tumors is an essential tool to evaluate the immune function of patients with immunodeficiency or autoimmunity. Therefore, this study aims to find the potential tumor antigen of LGG and identify the suitable population for cancer vaccination based on the immune landscape.MethodThe genomic and clinical data of 529 patients with LGG were obtained from TCGA, the mRNA_seq data of normal brain tissue were downloaded from GTEx. Differential expression gene and mutation analysis were performed to screen out potential antigens, K-M curves were carried out to investigate the correlation between the level of potential antigens and OS and DFS of patients. TIMER dataset was used to explore the correlation between genes and immune infiltrating cells. Immunophenotyping of 529 tumor samples was based on the single-sample gene sets enrichment analysis. Cibersort and Estimate algorithm were used to explore the tumor immune microenvironment characteristics in each immune subtype. Weighted gene co-expression network analysis (WGCNA) clustered immune-related genes and screened the hub genes, and pathway enrichment analyses were performed on the hub modules related to immune subtype in the WGCNA.ResultsSelecting for the mutated, up-regulated, prognosis- and immune-related genes, four potential tumor antigens were identified in LGG. They were also significantly positively associated with the antigen-presenting immune cells (APCs). Three robust immune subtypes, IS1, IS2 and IS3, represented immune status "desert", "immune inhibition", and "inflamed" respectively, which might serve as a predictive parameter. Subsequently, clinicopathological features, including the codeletion status of 1p19q, IDH mutation status, tumor mutation burden, tumor stemness, etc., were significantly different among subtypes.ConclusionFCGBP, FLNC, TLR7, and CSF2RA were potential antigens for developing cancer vaccination, and the patients in IS3 were considered the most suitable for vaccination in LGG.
| S-EPMC8369324 | biostudies-literature
Project description:Purpose: The applicability of mRNA vaccines against esophageal squamous cell carcinoma (ESCC) remains unclear. Here, we identified potential antigens for developing mRNA vaccines against ESCC and characterized immune subtypes to select appropriate patients for vaccination. Methods: RNA-seq, genetic alteration data, and corresponding clinical information of ESCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The RNA-seq data of normal esophageal tissue were obtained from the Genotype-Tissue Expression (GTEx) database. Potential tumor antigens were screened by analyzing differentially expressed and mutated genes and potential antigens with significant differences in prognosis were screened using the Kaplan-Meier method. The proportion of immune cell infiltration in the tumor microenvironment was estimated using CIBERSORT and MCPcounter, and the correlation of potential antigens with antigen-presenting cells and major histocompatibility complex class II was analyzed. Subsequently, immune subtypes were constructed using consensus clustering analysis and characterized by single-sample gene set enrichment analysis and weighted gene co-expression network analysis (WGCNA). The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to analyze the drug sensitivity of different immune subtypes. Results: Four overexpressed and mutated tumor antigens associated with antigen presentation and poor prognosis were identified in ESCC, including NLRC5, FCRL4, TMEM229B, and LCP2. By consensus clustering, we identified two immune-associated ESCC subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2); the prognosis of the two subtypes was statistically different. In addition, the two immune subtypes had distinctly different cellular, molecular, and clinical characteristics. IS1 patients have a distinct immune "hot" phenotype with strong immune tolerance, whereas patients with IS2 have an immune "cold" phenotype. Differential expression of immune checkpoints and immunogenic cell death modulators was observed between the different immune subtypes. Finally, we found that IS1 and IS2 patients showed different drug sensitivities to common anti-tumor drugs, possibly facilitating the development of individualized treatment regimens for patients. Conclusion: NLRC5, LCP2, TMEM229B, and FCRL4 are potential antigens for ESCC mRNA vaccines, and such vaccines may be more suitable for IS2 patients. This study provides a theoretical basis for mRNA vaccines against ESCC, by identifying the critical characteristics to predict ESCC prognosis and select suitable patients for vaccination.
| S-EPMC9207414 | biostudies-literature
Project description:mRNA vaccines have become a promising alternative to conventional cancer immunotherapy approaches. However, its application on colorectal cancer (CRC) remains poorly understood. We herein identified potential antigens for designing an effective mRNA vaccine, further to build an immune landscape for the accurate selection of patients for mRNA vaccine therapy. Raw transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were retrieved. Consensus clustering algorithm was applied to divide the CRC samples into four immune subtypes. Immunogenomics analysis was further integrated to characterize the immune microenvironment of each immune subtype. Six tumor antigens were found to be associated with poor prognosis and infiltration of antigen-presenting cells (APCs) in CRC patients. Furthermore, each of the immune subtypes showed differential cellular and molecular features. The IS2 and IS4 exhibited significantly improved survival and higher immune cell infiltration compared with IS1 and IS3. Immune checkpoint molecules and human leukocyte antigen also showed significant differential expression in four immune subtypes. Moreover, we performed graph structure learning-based dimensionality reduction to visualize the immune landscape of CRC. Our results revealed a complex immune landscape that may provide directions for mRNA vaccine treatment of CRC and define appropriate vaccination patients.
| S-EPMC8811447 | biostudies-literature
Project description:BackgroundNowadays, researchers are leveraging the mRNA-based vaccine technology used to develop personalized immunotherapy for cancer. However, its application against glioma is still in its infancy. In this study, the applicable candidates were excavated for mRNA vaccine treatment in the perspective of immune regulation, and suitable glioma recipients with corresponding immune subtypes were further investigated.MethodsThe RNA-seq data and clinical information of 702 and 325 patients were recruited from TCGA and CGGA, separately. The genetic alteration profile was visualized and compared by cBioPortal. Then, we explored prognostic outcomes and immune correlations of the selected antigens to validate their clinical relevance. The prognostic index was measured via GEPIA2, and infiltration of antigen-presenting cells (APCs) was calculated and visualized by TIMER. Based on immune-related gene expression, immune subtypes of glioma were identified using consensus clustering analysis. Moreover, the immune landscape was visualized by graph learning-based dimensionality reduction analysis.ResultsFour glioma antigens, namely ANXA5, FKBP10, MSN, and PYGL, associated with superior prognoses and infiltration of APCs were selected. Three immune subtypes IS1-IS3 were identified, which fundamentally differed in molecular, cellular, and clinical signatures. Patients in subtypes IS2 and IS3 carried immunologically cold phenotypes, whereas those in IS1 carried immunologically hot phenotype. Particularly, patients in subtypes IS3 and IS2 demonstrated better outcomes than that in IS1. Expression profiles of immune checkpoints and immunogenic cell death (ICD) modulators showed a difference among IS1-IS3 tumors. Ultimately, the immune landscape of glioma elucidated considerable heterogeneity not only between individual patients but also within the same immune subtype.ConclusionsANXA5, FKBP10, MSN, and PYGL are identified as potential antigens for anti-glioma mRNA vaccine production, specifically for patients in immune subtypes 2 and 3. In summary, this study may shed new light on the promising approaches of immunotherapy, such as devising mRNA vaccination tailored to applicable glioma recipients.
| S-EPMC8429949 | biostudies-literature