Discovering ferroptosis-associated tumor antigens and ferroptosis subtypes in pancreatic adenocarcinoma to facilitate mRNA vaccine development
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ABSTRACT:
SUBMITTER: Yan T
PROVIDER: S-EPMC10923709 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
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Project description:mRNA vaccines are becoming a feasible alternative for treating cancer. To develop mRNA vaccines against LUAD, potential antigens were identified and LUAD ferroptosis subtypes distinguished for selecting appropriate patients. The genome expression omnibus, cancer genome atlas (TCGA) and FerrDB were used to collect gene expression profiles, clinical information, and the genes involved in ferroptosis, respectively. cBioPortal was used to visualize and compare genetic alterations, GEPIA2 to calculate prognostic factors of the selected antigens, and TIMER to visualize the relationship between potential antigens and tumor immune cell infiltration. Consensus clustering analysis was utilized to identify ferroptosis subtypes and their prognostic value assessed by Log-rank and cox regression tests. The modules of ferroptosis-related gene screening were conducted by weight gene co-expression network analysis. The LUAD ferroptosis landscape was visualized through dimensionality reduction and graph learning. Six tumor antigens had obvious LUAD-mutations, positively correlated with different antigen-presenting cells, and might induce tumor cell ferroptosis. LUAD patients were stratified into three ferroptosis subtypes (FS1, FS2, and FS3) according to diverse molecular, cellular, and clinical characteristics. FS3 showed the highest tumor mutation burden and the most somatic mutations, deemed potential indicators of mRNA vaccine effectiveness. Moreover, different ferroptosis subtypes expressed distinct immune checkpoints and immunogenic cell death modulators. AGPS, NRAS, MTDH, PANX1, NOX4, and PPARD are potentially suitable for mRNA vaccinations against LUAD, specifically in patients with FS3 tumors. This study defines vaccination candidates and establishes a theoretical basis for LUAD mRNA vaccinations.
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Project description:Cancer vaccines are emerging as a viable strategy for cancer treatment. In the current study, we screened for genes associated with the prognosis of patients with lung adenocarcinoma and positively correlated with antigen-presenting cell infiltration and identified KLRG1 and CBFA2T3 as potential tumor antigens for mRNA vaccines in lung adenocarcinoma (LUAD). Further analyses of immune subtypes revealed that patients with early-stage LUAD, high immune cell infiltration, high immune checkpoint expression, and low tumor mutation burden might benefit from mRNA vaccination. Moreover, we identified four biomarkers that can be used to assess mRNA vaccination suitability. We also identified potentially sensitive anti-cancer drugs for populations not suitable for vaccination by means of anti-cancer drug susceptibility prediction. Overall, we provided a new perspective for mRNA vaccine treatment strategies for LUAD and emphasized the importance of precise and personalized treatments.
| S-EPMC8899518 | biostudies-literature
Project description:The mRNA vaccine has provided a promising approach for cancer immunotherapies. However, only a few mRNA vaccines have been developed against colon adenocarcinoma (COAD). Screening potential targets for mRNA vaccines from numerous candidates is a substantial challenge. Considering the tumor heterogeneity, only a subset of patients might respond to vaccinations. This study was conducted to identify potential candidates for mRNA vaccines, and distinguish appropriate subgroups of COAD patients for vaccination. A total of five tumor antigens with prognostic values were identified, including IGF2BP3, DPCR1, HOXD10, TRIM7, and ZIC5. The COAD patients were stratified into five immune subtypes (IS1-IS5), according to consensus clustering analysis. Higher tumor mutation burden (TMB) was observed in IS1 and IS5 subtypes. The IS1 and IS5 subtypes have shown the baseline of immune-hot tumor microenvironment, while other subtypes displayed immune desert phenotype. Distinct expressions of immune checkpoints (ICPs)-related genes and immunogenic cell death (ICD) modulators were observed among five immune subtypes. Finally, the immune landscape was conducted to narrow the immune components for better personalized mRNA-based vaccination. The IFIT3, PARP9, TAP1, STAT1, and OAS2 were confirmed as hub genes, and COAD patients with higher expressions of these genes might be more appropriate for mRNA vaccination. In conclusion, the IGF2BP3, DPCR1, HOXD10, TRIM7, and ZIC5 were identified as potential candidates for developing mRNA vaccines against COAD, and patients in IS1 and IS5 subtypes might respond better to mRNA vaccination.
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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:BackgroundThe mRNA vaccine has become a promising platform for cancer therapy. Lots of studies have been focusing on discovering novel potent cancer-associated antigens to develop mRNA vaccines against cancers. Besides, immunotyping shows the immune status, and immune microenvironment of immunotyping is related with therapeutic reaction. However, potential antigens for mRNA vaccines and immunotyping of liver hepatocellular carcinoma (LIHC) remain far from being understood.MethodsIn this study, we collected gene expression data and clinical information data from ICGC and TCGA databases. Using GEPIA2, we calculated differential expression genes and prognostic indices. We applied TIMER to calculate the correlation coefficient between immune infiltrating cells and each gene. Consensus cluster was used for immunotyping of LIHC.ResultsWe uncovered four most potential candidates including PES1, MCM3, PPM1G, and KPNA2, which were all related with antigen-presenting cell (APC) infiltration and poor survival in LIHC in two independent datasets. Furthermore, three immune-related subtypes (IS1-IS3) of LIHC were identified. All these results were validated in two independent datasets. Furthermore, we validated our results in vitro.ConclusionsThe above candidates will be expected to be potential antigen genes for developing anti-LIHC mRNA vaccine, and furthermore, patients with IS2 and IS3 tumors are supposed to be appropriate for mRNA vaccine in LIHC.
| S-EPMC9444406 | biostudies-literature
Project description:Prostate adenocarcinoma (PRAD) is a leading cause of death among men. Messenger ribonucleic acid (mRNA) vaccine presents an attractive approach to achieve satisfactory outcomes; however, tumor antigen screening and vaccination candidates show a bottleneck in this field. We aimed to investigate the tumor antigens for mRNA vaccine development and immune subtypes for choosing appropriate patients for vaccination. We identified eight overexpressed and mutated tumor antigens with poor prognostic value of PRAD, including KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3. The correlation of those genes with antigen-presenting immune cells were assessed. We further identified three immune subtypes of PRAD (PRAD immune subtype [PIS] 1-3) with distinct clinical, molecular, and cellular characteristics. PIS1 showed better survival and immune cell infiltration, nevertheless, PIS2 and PIS3 showed cold tumor features with poorer prognosis and higher tumor genomic instability. Moreover, these immune subtypes presented distinguished association with immune checkpoints, immunogenic cell death modulators, and prognostic factors of PRAD. Furthermore, immune landscape characterization unraveled the immune heterogeneity among patients with PRAD. To summarize, our study suggests KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3 are potential antigens for PRAD mRNA vaccine development, and patients in the PIS2 and PIS3 groups are more suitable for vaccination.
| S-EPMC8645679 | 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.
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Project description:The use of vaccines for cancer therapy is a promising immunotherapeutic strategy that has been shown to be effective against various cancers. Vaccines directly target tumors but their efficacy against glioblastoma multiforme (GBM) remains unclear. Immunotyping that classifies tumor samples is considered to be a biomarker for immunotherapy. This study aimed to identify potential GBM antigens suitable for vaccine development and develop a tool to predict the response of GBM patients to vaccination based on the immunotype. Gene Expression Profiling Interactive Analysis (GEPIA) was applied to evaluate the expression profile of GBM antigens and their influence on clinical prognosis, while the cBioPortal program was utilized to integrate and analyze genetic alterations. The correlation between antigens and antigen processing cells was assessed using TIMER. RNA-seq data of GBM samples and their corresponding clinical data were downloaded from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) for further clustering analysis. Six overexpressed and mutated tumor antigens (ARHGAP9, ARHGAP30, CLEC7A, MAN2B1, ARPC1B and PLB1) were highly correlated with the survival rate of GBM patients and the infiltration of antigen presenting cells in GBMs. With distinct cellular and molecular characteristics, three immune subtypes (IS1-IS3) of GBMs were identified and GBMs from IS3 subtype were more likely to benefit from vaccination. Through graph learning-based dimensional reduction, immune landscape was depicted and revealed the existence of heterogeneity among individual GBM patients. Finally, WGCNA can identify potential vaccination biomarkers by clustering immune related genes. In summary, the six tumor antigens are potential targets for developing anti-GBMs mRNA vaccine, and the immunotypes can be used for evaluating vaccination response.
| S-EPMC8847306 | 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:BackgroundAlthough mRNA vaccines have been efficient for combating a variety of tumors, their effectiveness against glioma remains unclear. There is growing evidence that immunophenotyping can reflect the comprehensive immune status and microenvironment of the tumor, which correlates closely with treatment response and vaccination potency. The purpose of this research was to screen for effective antigens in glioma that could be used for developing mRNA vaccines and to further differentiate the immune subtypes of glioma to create an selection criteria for suitable patients for vaccination.MethodsGene expression profiles and clinical data of 698 glioma samples were extracted from The Cancer Genome Atlas, and RNA_seq data of 1018 glioma samples was gathered from Chinese Glioma Genome Atlas. Gene Expression Profiling Interactive Analysis was used to determine differential expression genes and prognostic markers, cBioPortal software was used to verify gene alterations, and Tumor Immune Estimation Resource was used to investigate the relationships among genes and immune infiltrating cells. Consistency clustering was applied for consistent matrix construction and data aggregation, Gene oncology enrichment was performed for functional annotation, and a graph learning-based dimensionality reduction method was applied to describe the subtypes of immunity.ResultsFour overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in glioma, including TP53, IDH1, C3, and TCF12. Besides, four immune subtypes of glioma (IS1-IS4) and 10 immune gene modules were identified consistently in the TCGA data. The immune subtypes had diverse molecular, cellular, and clinical features. IS1 and IS4 displayed an immune-activating phenotype and were associated with worse survival than the other two subtypes, while IS2 and IS3 had lower levels of tumor immune infiltration. Immunogenic cell death regulators and immune checkpoints were also diversely expressed in the four immune subtypes.ConclusionTP53, IDH1, C3, and TCF12 are effective antigens for the development of anti-glioma mRNA vaccines. We found four stable and repeatable immune subtypes of human glioma, the classification of the immune subtypes of glioma may play a crucial role in the predicting mRNA vaccine outcome.
| S-EPMC8484904 | biostudies-literature