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Background: Tumor mRNA vaccines have been identified as a promising technology for cancer therapy in multiple cancer types, while their efficacy in thyroid cancer (THCA) is unclear. Immunotyping is strongly associated with the immune microenvironment and immune status in cancer, thus it is important in vaccination and therapeutic response. This study is to identify potential valuable antigens and novel immune subtypes of THCA for immune landscape construction, thus screening patients suitable for mRNA vaccination. Methods: The clinical information and gene expression files of 568 THCA cases were obtained from the TCGA dataset. The DNA copy number variation and the somatic mutation of THCA were visualized by the cBioPortal database. TIMER was used to investigate the immune infiltrating correlation with candidate antigens. Consensus clustering analysis was conducted to cluster data using the ConsensusClusterPlus package. The immune landscapes of THCA patients were visualized using the Monocle package. The critical hub genes for THCA mRNA vaccines were identified by WGCNA package. To validate, the immunohistochemistry and real-time quantitative PCR (RT-qPCR) were performed to detect the expression level of potential antigen for mRNA vaccine in tissue and cell lines in THCA. Results: Thymidine kinase 1 (TK1) was identified as a potential biomarker of mRNA vaccine against THCA. It was confirmed to be significantly upregulated in THCA tissues and cells lines. Moreover, three novel immune subtypes of THCA were obtained based on the expression consistency of immune-associated genes. The S2 subtype was characterized as an immunological "cold" phenotype with a high expression of immunogenic cell death modulators. S1 and S3 subtypes were immunological "hot" phenotypes with immune checkpoints upregulation. Further, the immune landscape of THCA patients was visualized and ten hub genes for mRNA vaccines were identified. Conclusion: TK1 was a tumor-specific antigen of mRNA vaccines. The patients belonging to the S2 subtype ("cold" tumor) were suitable for mRNA vaccine therapy in THCA. Notably, ten hub genes were conducted as potential biomarkers for identifying suitable patients for mRNA vaccination. These findings provided novel insights into mRNA vaccine development against THCA. [ABSTRACT FROM AUTHOR]

Background In this study, effective antigens of mRNA vaccine were excavated from the perspective of ICD, and ICD subtypes of PRAD were further distinguished to establish an ICD landscape, thereby determining suitable vaccine recipients.Research design and methods TCGA and MSKCC databases were applied to acquire RNA-seq data and corresponding clinical data of 554 and 131 patients, respectively. GEPIA was employed to measure prognostic indices. Then, a comparison of genetic alterations was performed utilizing cBioPortal, and correlation of identified ICD antigens with immune infiltrating cells was analyzed employing TIMER. Moreover, ICD subtypes were identified by means of consensus cluster, and ICD landscape of PRAD was depicted utilizing graph learning-based dimensional reduction.Results In total, 4 PRAD antigens were identified in PRAD, including FUS, LMNB2, RNPC3, and ZNF700, which had association with adverse prognosis and infiltration of APCs. PRAD patients were classified as two ICD subtypes based on their differences in molecular, cellular, and clinical features. Furthermore, ICD modulators and immune checkpoints were also differentially expressed between two ICD subtype tumors. Finally, the ICD landscape of PRAD showed substantial heterogeneity among individual patients.Conclusions In summary, the research may provide a theoretical foundation for developing mRNA vaccine against PRAD as well as determining appropriate vaccine recipients.

Background Perturbation of gut microbiota has been linked to chronic kidney disease (CKD), which was correlated with a sophisticated milieu of metabolic and immune dysregulation. Methods To clarify the underlying host–microbe interaction in CKD, we performed multi-omics measurements, including systems-level gut microbiome, targeted serum metabolome and deep immunotyping, in a cohort of patients and non-CKD controls. Results Our analyses on functional profiles of the gut microbiome showed a decrease in the diversity and abundance of carbohydrate-active enzyme (CAZyme) genes but an increase in the abundance of antibiotic resistance, nitrogen cycling enzyme and virulence factor genes in CKD. Moreover, models generated using measurements of serum metabolites (amino acids, bile acids and short-chain fatty acids) or immunotypes were predictive of renal impairment but less so than many of the functional profiles derived from gut microbiota, with the CAZyme genes being the top-performing model to accurately predict the early stage of diseases. In addition, co-occurrence analyses revealed coordinated host–microbe relationships in CKD. Specifically, the highest fractions of significant correlations were identified with circulating metabolites by several taxonomic and functional profiles of gut microbiome, while immunotype features were moderately associated with the abundance of microbiome-encoded metabolic pathways and serum levels of amino acids (e.g. B cell cluster tryptophan and B cell cluster tryptophan metabolism). Conclusion Overall, our multi-omics integration revealed several signatures of systems-level gut microbiome in robust associations with host–microbe co-metabolites and renal function, which may have aetiological and diagnostic implications in CKD. [ABSTRACT FROM AUTHOR]

The low response rate to immunosuppressant is mainly due to the lack of adequate knowledge about the tumor microenvironment (TME) and screening biomarkers for gliomas. We aimed to identify the promising immune biomarkers and new immune classification of glioma. In this study, multiple‐immune algorithms were used to calculate immune‐infiltration scores. Unsupervised and supervised machine learning methods were used to perform the classification. We observed that OLFML3 overexpression was indicated in gliomas and linked to poor prognosis. OLFML3 knockdown inhibited proliferation, invasion and increased the sensitivity of glioma cells to temozolomide. OLFML3 expression could also reflect the aberrant immune status. Based on the immune‐related signature, patients were divided into three immune subtypes via consensus clustering. Patients with C2 subtype presented poorer prognosis and shorter progression free survival than patients with other two subtypes. The TME patterns among subtypes were different. C2 and C3 subtypes are the immune‐inflamed and immune‐desert tumors, respectively. Additionally, compared with C3 subtype, patients with C1/C2 subtypes were more likely to respond to immunotherapy. The pRRophetic algorithm indicated patients with C1/C2 subtypes were more resistant to temozolomide, but sensitive to paclitaxel and cisplatin. To conclude, OLFML3 overexpression affects glioma cell proliferation, invasion, and TMZ sensitivity and has been proved to be an independent prognostic‐ and immune‐related biomarker. Additionally, the novel immune subtype's classification could provide the prognostic and predictive predictors for glioma patients and may guide physicians in selecting potential responders. [ABSTRACT FROM AUTHOR]

Abstract 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.

Abstract The low response rate to immunosuppressant is mainly due to the lack of adequate knowledge about the tumor microenvironment (TME) and screening biomarkers for gliomas. We aimed to identify the promising immune biomarkers and new immune classification of glioma. In this study, multiple‐immune algorithms were used to calculate immune‐infiltration scores. Unsupervised and supervised machine learning methods were used to perform the classification. We observed that OLFML3 overexpression was indicated in gliomas and linked to poor prognosis. OLFML3 knockdown inhibited proliferation, invasion and increased the sensitivity of glioma cells to temozolomide. OLFML3 expression could also reflect the aberrant immune status. Based on the immune‐related signature, patients were divided into three immune subtypes via consensus clustering. Patients with C2 subtype presented poorer prognosis and shorter progression free survival than patients with other two subtypes. The TME patterns among subtypes were different. C2 and C3 subtypes are the immune‐inflamed and immune‐desert tumors, respectively. Additionally, compared with C3 subtype, patients with C1/C2 subtypes were more likely to respond to immunotherapy. The pRRophetic algorithm indicated patients with C1/C2 subtypes were more resistant to temozolomide, but sensitive to paclitaxel and cisplatin. To conclude, OLFML3 overexpression affects glioma cell proliferation, invasion, and TMZ sensitivity and has been proved to be an independent prognostic‐ and immune‐related biomarker. Additionally, the novel immune subtype's classification could provide the prognostic and predictive predictors for glioma patients and may guide physicians in selecting potential responders.

Background: To screen efficacious neoantigens for the development of LIHC mRNA vaccines, construct LIHC immune clusters, and therefore select patients who might benefit from vaccination. Methods: RNA-seq data and clinical information of 371 TCGA-LIHC and 231 ICGC-LIHC cohorts were downloaded. Differentially expressed genes and their associations with prognosis were analyzed by GEPIA, genetic alterations were examined in the cBioPortal portal, and the association between genes and immune infiltrating cells was explored by TIMER. The immune clusters were constructed by consistency clustering, and the immune landscape was described using CIBERSORT. Results: POLR3C and KPNA2 were identified as LIHC tumor neoantigens related to inferior prognosis and antigen-presenting cell infiltration. In addition, three immune clusters (IC1, IC2 and IC3) with significant differences in molecular, immune cytological, and clinical features were identified in both the TCGA and ICGC LIHC cohorts. Immune "hot" phenotype IC3 displayed a better survival than IC2, and immune "cold" phenotype IC1 exhibited a high tumor mutation burden. Conclusion: In conclusion, for the development of anti-LIHC mRNA vaccines, we identified efficacious neoantigens POLR3C and KPNA2, profiled the tumor microenvironment of LIHC, and identified IC1 patients as the subgroup who might not most benefit from vaccination. [ABSTRACT FROM AUTHOR]

Laboratory tests are significant for the detection of immunopathological disorders in kidney transplantation. As a rule, the choice of tests is carried out individually and is based on the clinical characteristics and the presumptive diagnosis. Most often, in patients after kidney transplantation, atypical and not always standard changes in immunological parameters are observed, which is associated with a combination of many factors leading to different immune responses. All this served as the basis for typing immunological parameters in renal allograft recipients using one of the methods of system analysis – cluster analysis. Kidney transplantation was performed in 104 recipients. Immunological examination was performed on the 360th day after the surgery. The following groups of recipients were identified: KTR1 – with primary graft function on the 7th day and satisfactory graft function within a year, KTR2 – with renal graft dysfunction on the 7th day and within a year. By means of cluster analysis, immunotypes of regulatory complexes were detected and characterized in various courses of the post-transplant period. To assess the immune response in allogeneic kidney transplantation, a set of immune cells with a phenotype should be determined: CD3+CD4+CD25+highCD127+low, CD3+CD4-CD8-, CD3+CD4+CD69+, CD3+CD16+CD56+, CD19+CD5+, LIN-HLA-DR+CD11c-CD123+, CD3+CD8+CD69+, CD3+CD4+CD8+, CD3+CD8+CD38+, CD19+CD86+, CD19+IgD+CD27-, CD3-CD16+CD56+, CD3+CD38+, CD14+lowCD86+, LIN-HLA-DR+CD11c+CD123-. According to our data, the immunological cellular composition of the central point of clustering of the tolerogenic immunological complex is represented by regulatory CD3+CD4+CD25+highCD127+low and double-negative CD3+CD4-CD8-T lymphocytes. The composition of the central point of clustering of the hyperergic immunological complex is represented by the cooperation of CD3+CD8+CD69+ and CD3+CD4+CD8+ cells. The structure of the tolerogenic immune response in patients after kidney transplantation is based on intercellular interactions, which has a hierarchical system, the basis of which is represented by the cooperation of regulatory cells CD3+CD4+CD25+highCD127+low, CD3+CD4-CD8-, CD3+CD4+CD69+, CD3+CD16+CD56+, CD19+CD5+, LIN-HLA-DR+CD11c-CD123+. The hyperergic variant of the immune response in renal allograft transplantation is based on excessive activation of the following links of the immune response: CD3+CD8+CD38+, CD19+CD86+, CD3+CD38+, LIN-HLADR+CD11c+CD123-, CD19+IgD+CD27-, CD3-CD16+CD56+, CD3+CD8+CD69+ and CD14+lowCD86+. The detected immunotypes will make it possible to implement a personalized approach to the diagnosis and treatment of patients with various types of immune response in kidney transplantation.

Background: Although mRNA vaccines have been effective against multiple cancers, their efficacy against stomach adenocarcinoma (STAD) remains undefined. Immunotyping can indicate the comprehensive immune status in tumors and their immune microenvironment, which is closely associated with therapeutic response and vaccination potential. The aim of this study was to identify potential antigens in STAD for mRNA vaccine development, and further distinguish immune subtypes of STAD to construct an immune landscape for selecting suitable patients for vaccination.Methods: The gene expression and clinicopathological features of patients with gastric cancer were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Program (GTEx). 729 samples from GSE66229 and GSE84437 were downloaded through GEO and were used as the validation cohorts. Differential gene expression, genetic alterations and prognosis were analyzed using the R package, cBioPortal program and Kaplan-Meier. The relationship between tumor antigens and immune cells was evaluated and plotted by TIMER. ConsensusClusterPlus was used for consistency matrix construction and data clustering, and graph learning-based dimensional reduction was used to depict immune landscape. WGCNA was used to estimate the relationship between the color modules and immune subtypes.Results: Two overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in STAD, including RAI14 and NREP. The immune subtypes showed distinct molecular, cellular and clinical characteristics. IS1 and IS2 exhibited immune-activated phenotypes and correlated to better survival compared to IS3, while IS3 tumors was immunologically cold. Immunogenic cell death modulators, immune checkpoints, and CA125, and CEA were also differentially expressed among the three immune subtypes. Finally, the immune landscape of STAD showed a high degree of heterogeneity between individual patients.Conclusion: RAI14 and NREP are potential antigens for developing anti-STAD mRNA vaccine, and patients with IS1 and IS3 tumors may be suitable for vaccination.

Background: Clear cell renal cell carcinoma (ccRCC) is a highly immunogenic tumor. The purpose of the present study was to establish a novel immunotype for different immune infiltration and overall survival (OS) of patients with ccRCC. Methods: Based on the Cancer Genome Atlas Project (TCGA) database (discovery set), a novel immunotype was established using ssGSEA methods. The databases of Fudan University Shanghai Cancer Center (FUSCC) and Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine (XHH) served as an external validation set. GSEA was carried out to identify the immunotype associated signal transduction pathways. Results: A total of 652 ccRCC patients were included in our study. We constructed a novel immunotype of ccRCC to classify patients into three groups: high-immunity, moderate-immunity, and low-immunity. The highimmunity and moderate-immunity groups had higher ImmuneScores, ESTIMATEScores, StromalScores, and lower tumor purity than that of the low-immunity group in both sets. Additionally, the patients from the highimmunity and moderate-immunity groups had longer survival than patients from low-immunity group in both discovery set and validation set (HR = 2.54, 95% CI: 1.56–4.13, p < 0.01; HR = 2.75, 95% CI: 1.24–6.11, p = 0.01). Conclusion: In summary, we defined a novel immunotype of ccRCC. The immune types could be used as a clinical predictive tool to identify ccRCC patients with different survival. In addition, the immune-related biological signaling pathway also brought new insights on the mechanism of ccRCC. [ABSTRACT FROM AUTHOR]

Background: Tumor mRNA vaccines have been identified as a promising technology for cancer therapy in multiple cancer types, while their efficacy in thyroid cancer (THCA) is unclear. Immunotyping is strongly associated with the immune microenvironment and immune status in cancer, thus it is important in vaccination and therapeutic response. This study is to identify potential valuable antigens and novel immune subtypes of THCA for immune landscape construction, thus screening patients suitable for mRNA vaccination., Methods: The clinical information and gene expression files of 568 THCA cases were obtained from the TCGA dataset. The DNA copy number variation and the somatic mutation of THCA were visualized by the cBioPortal database. TIMER was used to investigate the immune infiltrating correlation with candidate antigens. Consensus clustering analysis was conducted to cluster data using the ConsensusClusterPlus package. The immune landscapes of THCA patients were visualized using the Monocle package. The critical hub genes for THCA mRNA vaccines were identified by WGCNA package. To validate, the immunohistochemistry and real-time quantitative PCR (RT-qPCR) were performed to detect the expression level of potential antigen for mRNA vaccine in tissue and cell lines in THCA., Results: Thymidine kinase 1 ( TK1 ) was identified as a potential biomarker of mRNA vaccine against THCA. It was confirmed to be significantly upregulated in THCA tissues and cells lines. Moreover, three novel immune subtypes of THCA were obtained based on the expression consistency of immune-associated genes. The S2 subtype was characterized as an immunological "cold" phenotype with a high expression of immunogenic cell death modulators. S1 and S3 subtypes were immunological "hot" phenotypes with immune checkpoints upregulation. Further, the immune landscape of THCA patients was visualized and ten hub genes for mRNA vaccines were identified., Conclusion: TK1 was a tumor-specific antigen of mRNA vaccines. The patients belonging to the S2 subtype ("cold" tumor) were suitable for mRNA vaccine therapy in THCA. Notably, ten hub genes were conducted as potential biomarkers for identifying suitable patients for mRNA vaccination. These findings provided novel insights into mRNA vaccine development against THCA., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Wang, Xu, Li, Song, Liu, Tian, Wang, Zhao and Wang.)

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. [ABSTRACT FROM AUTHOR]

Abstract Background Although mRNA vaccines have been effective against multiple cancers, their efficacy against pancreatic adenocarcinoma (PAAD) remains undefined. Accumulating evidence suggests that immunotyping can indicate the comprehensive immune status in tumors and their immune microenvironment, which is closely associated with therapeutic response and vaccination potential. The aim of this study was to identify potent antigens in PAAD for mRNA vaccine development, and further distinguish immune subtypes of PAAD to construct an immune landscape for selecting suitable patients for vaccination. Methods Gene expression profiles and clinical information of 239 PAAD datasets were extracted from ICGC, and RNA-Seq data of 103 samples were retrieved from TCGA. GEPIA was used to calculate differential expression levels and prognostic indices, cBioPortal program was used to compare genetic alterations, and TIMER was used to explore correlation between genes and immune infiltrating cells. Consensus cluster was used for consistency matrix construction and data clustering, DAVID was used for functional annotation, and graph learning-based dimensional reduction was used to depict immune landscape. Results Six overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in PAAD, including ADAM9, EFNB2, MET, TMOD3, TPX2, and WNT7A. Furthermore, five immune subtypes (IS1-IS5) and nine immune gene modules of PAAD were identified that were consistent in both patient cohorts. The immune subtypes showed distinct molecular, cellular and clinical characteristics. IS1 and IS2 exhibited immune-activated phenotypes and correlated to better survival compared to the other subtypes. IS4 and IS5 tumors were immunologically cold and associated with higher tumor mutation burden. Immunogenic cell death modulators, immune checkpoints, and CA125 and CA199, were also differentially expressed among the five immune subtypes. Finally, the immune landscape of PAAD showed a high degree of heterogeneity between individual patients. Conclusions ADAM9, EFNB2, MET, TMOD3, TPX2, and WNT7A are potent antigens for developing anti-PAAD mRNA vaccine, and patients with IS4 and IS5 tumors are suitable for vaccination.

Background: The cytokine profile of atopic dermatitis (AD) depends on age, ethnicity, and disease severity. This study examined biomarkers in children with AD collected by tape strips and skin biopsies, and examined whether the levels differed with filaggrin genotype, disease severity, and food allergy. Methods: Twenty‐five children aged 2–14 years with AD were clinically examined. Skin biopsies were collected from lesional skin and tape strips were collected from lesional and non‐lesional skin. We analyzed natural moisturizing factor (NMF) and 17 immune markers represented by mRNA levels in skin biopsies and protein levels in tape strips. Common filaggrin gene mutations were examined in all children. Results: The cytokine profile in lesional skin was dominated by a T helper (Th) 2 response in skin biopsies, and by a general increase in innate inflammation markers (interleukin (IL)‐1α, IL‐1β, IL‐8, IL‐18) along with TARC and CTACK in tape strips. The levels of TARC, CTACK, IL‐8, IL‐18 showed significant correlation with AD severity in both lesional and non‐lesional tape stripped skin, while no significant correlations were observed in skin biopsy data. In tape strips from lesional and non‐lesional skin, the levels of NMF and selected cytokines differed significantly between children with and without FLG mutations and food allergy. Conclusion: Sampling of the stratum corneum with non‐invasive tape strips can be used to identify biomarkers that are associated with disease severity, food allergy and FLG mutations. Skin biopsies showed robust Th2 signature but was inferior for association analysis regarding severity. [ABSTRACT FROM AUTHOR]

Background: Messenger ribonucleic acid (mRNA) vaccine has been considered as a potential therapeutic strategy and the next research hotspot, but their efficacy against prostate adenocarcinoma (PRAD) remains undefined. This study aimed to find potential antigens of PRAD for mRNA vaccine development and identify suitable patients for vaccination through immunophenotyping. Methods: Gene expression profiles and clinical information were obtained from TCGA and ICGC. GEPIA2 was used to calculate the prognostic index of the selected antigens. The genetic alterations were compared on cBioPortal and the correlation between potential antigen and immune infiltrating cells was explored by TIMER. ConsensusClusterPlus was used to construct a consistency matrix, and identify the immune subtypes. Graph learning-based dimensional reduction was performed to depict immune landscape. Boruta algorithm and LASSO logistic analysis were used to screen PRAD patients who may benefit from mRNA vaccine. Results: Seven potential tumor antigens selected were significantly positively associated with poor prognosis and the antigen-presenting immune cells (APCs) in PRAD, including ADA, FYN, HDC, NFKBIZ, RASSF4, SLC6A3, and UPP1. Five immune subtypes of PRAD were identified by differential molecular, cellular, and clinical characteristics in both cohorts. C3 and C5 had immune "hot" and immunosuppressive phenotype, On the contrary, C1&C2 had immune "cold" phenotype. Finally, the immune landscape characterization showed the immune heterogeneity among patients with PRAD. Conclusions: ADA, FYN, HDC, NFKBIZ, RASSF4, SLC6A3, and UPP1 are potential antigens for mRNA vaccine development against PRAD, and patients in type C1 and C2 are suitable for vaccination. [ABSTRACT FROM AUTHOR]

Glioma is the most common primary malignant brain tumor in adults with very poor prognosis. The limited new therapeutic strategies for glioma patients can be partially attributed to the complex tumor microenvironment. However, knowledge about the glioma immune microenvironment and the associated regulatory mechanisms is still lacking. In this study, we found that, different immune subtypes have a significant impact on patient survival. Glioma patients with a high immune response subtype had a shorter survival compared with patients with a low immune response subtype. Moreover, the number of B cell, T cell, NK cell, and in particular, the macrophage in the immune microenvironment of patients with a high immune response subtype were significantly enhanced. In addition, 132 genes were found to be related to glioma immunity. The functional analysis and verification of seven core genes showed that their expression levels were significantly correlated with the prognosis of glioma patients, and the results were consistent at tissue levels. These findings indicated that the glioma immune microenvironment was significantly correlated with the prognosis of glioma patients and multiple genes were involved in regulating the progression of glioma. The identified genes could be used to stratify glioma patients based on immune subgroup analysis, which may guide their clinical treatment regimen. [ABSTRACT FROM AUTHOR]

Abstract Immunotherapy, especially anti-PD-1, is becoming a pillar of modern muscle-invasive bladder cancer (MIBC) treatment. However, the objective response rates (ORR) are relatively low due to the lack of precise biomarkers to select patients. Herein, the molecular subtype, tumor mutation burden (TMB), and CD8+ T cells were calculated by the gene expression and mutation profiles of MIBC patients. MIBC immunotypes were constructed using clustering analysis based on tumor mutation burden, CD8+ T cells, and molecular subtypes. Mutated genes, enriched functional KEGG pathways and GO terms, and co-expressed network-specific hub genes have been identified. We demonstrated that ORR of immunotype A patients identified by molecular subtype, CD8+ T cells, and TMB is about 36% predictable. PIK3CA, RB1, FGFR3, KMT2C, MACF1, RYR2, and EP300 are differentially mutated among three immunotypes. Pathways such as ECM-receptor interaction, PI3K-Akt signaling pathway, and TGF-beta signaling pathway are top-ranked in enrichment analysis. Low expression of ACTA2 was associated with the MIBC survival benefit. The current study constructs a model that could identify suitable MIBC patients for immunotherapy, and it is an important step forward to the personalized treatment of bladder cancers.

Glioma is the most common primary malignant brain tumor in adults with very poor prognosis. The limited new therapeutic strategies for glioma patients can be partially attributed to the complex tumor microenvironment. However, knowledge about the glioma immune microenvironment and the associated regulatory mechanisms is still lacking. In this study, we found that, different immune subtypes have a significant impact on patient survival. Glioma patients with a high immune response subtype had a shorter survival compared with patients with a low immune response subtype. Moreover, the number of B cell, T cell, NK cell, and in particular, the macrophage in the immune microenvironment of patients with a high immune response subtype were significantly enhanced. In addition, 132 genes were found to be related to glioma immunity. The functional analysis and verification of seven core genes showed that their expression levels were significantly correlated with the prognosis of glioma patients, and the results were consistent at tissue levels. These findings indicated that the glioma immune microenvironment was significantly correlated with the prognosis of glioma patients and multiple genes were involved in regulating the progression of glioma. The identified genes could be used to stratify glioma patients based on immune subgroup analysis, which may guide their clinical treatment regimen.

Background: Messenger ribonucleic acid (mRNA) vaccine has been considered as a potential therapeutic strategy and the next research hotspot, but their efficacy against prostate adenocarcinoma (PRAD) remains undefined. This study aimed to find potential antigens of PRAD for mRNA vaccine development and identify suitable patients for vaccination through immunophenotyping.Methods: Gene expression profiles and clinical information were obtained from TCGA and ICGC. GEPIA2 was used to calculate the prognostic index of the selected antigens. The genetic alterations were compared on cBioPortal and the correlation between potential antigen and immune infiltrating cells was explored by TIMER. ConsensusClusterPlus was used to construct a consistency matrix, and identify the immune subtypes. Graph learning-based dimensional reduction was performed to depict immune landscape. Boruta algorithm and LASSO logistic analysis were used to screen PRAD patients who may benefit from mRNA vaccine.Results: Seven potential tumor antigens selected were significantly positively associated with poor prognosis and the antigen-presenting immune cells (APCs) in PRAD, including ADA, FYN, HDC, NFKBIZ, RASSF4, SLC6A3, and UPP1. Five immune subtypes of PRAD were identified by differential molecular, cellular, and clinical characteristics in both cohorts. C3 and C5 had immune “hot” and immunosuppressive phenotype, On the contrary, C1&C2 had immune “cold” phenotype. Finally, the immune landscape characterization showed the immune heterogeneity among patients with PRAD.Conclusions: ADA, FYN, HDC, NFKBIZ, RASSF4, SLC6A3, and UPP1 are potential antigens for mRNA vaccine development against PRAD, and patients in type C1 and C2 are suitable for vaccination.

Background: Although mRNA vaccines have been effective against multiple cancers, their efficacy against pancreatic adenocarcinoma (PAAD) remains undefined. Accumulating evidence suggests that immunotyping can indicate the comprehensive immune status in tumors and their immune microenvironment, which is closely associated with therapeutic response and vaccination potential. The aim of this study was to identify potent antigens in PAAD for mRNA vaccine development, and further distinguish immune subtypes of PAAD to construct an immune landscape for selecting suitable patients for vaccination. Methods: Gene expression profiles and clinical information of 239 PAAD datasets were extracted from ICGC, and RNA-Seq data of 103 samples were retrieved from TCGA. GEPIA was used to calculate differential expression levels and prognostic indices, cBioPortal program was used to compare genetic alterations, and TIMER was used to explore correlation between genes and immune infiltrating cells. Consensus cluster was used for consistency matrix construction and data clustering, DAVID was used for functional annotation, and graph learning-based dimensional reduction was used to depict immune landscape. Results: Six overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in PAAD, including ADAM9, EFNB2, MET, TMOD3, TPX2, and WNT7A. Furthermore, five immune subtypes (IS1-IS5) and nine immune gene modules of PAAD were identified that were consistent in both patient cohorts. The immune subtypes showed distinct molecular, cellular and clinical characteristics. IS1 and IS2 exhibited immune-activated phenotypes and correlated to better survival compared to the other subtypes. IS4 and IS5 tumors were immunologically cold and associated with higher tumor mutation burden. Immunogenic cell death modulators, immune checkpoints, and CA125 and CA199, were also differentially expressed among the five immune subtypes. Finally, the immune landscape of PAAD showed a high degree of heterogeneity between individual patients. Conclusions: ADAM9, EFNB2, MET, TMOD3, TPX2, and WNT7A are potent antigens for developing anti-PAAD mRNA vaccine, and patients with IS4 and IS5 tumors are suitable for vaccination. [ABSTRACT FROM AUTHOR]

Background: Immunotherapies including PD-1/PD-L1 antibodies have been approved for the treatment of Muscle-invasive Bladder Cancer (MIBC) patients. However, immunotherapies could only be beneficial for about 20% MIBC patients. Thus, identification of the immune subtype is becoming increasingly important. This study aimed to explore the immune subtype by analyzing the gene expression profiles. Methods: A total of 6 datasets including (GSE13507, GSE31684, GSE32548, GSE32894, GSE69795, and TCGA-BLCA) were downloaded. The gene expression profiles from different datasets were combined since the batch effects were removed. We performed unsupervised clustering analysis to identify the immune subtype by the combined gene expression profiles. The tumor-infiltration levels of 22 immune cells, immune scores, and tumor purity were calculated, and the survival analysis was performed to investigate the prognosis difference between immune subtypes. The enriched pathways for each immune subtype were obtained. Results: We identified four novel immune subtypes (referred to S1, S2, S3, and S4) among MIBC patients. We found that S1 was enriched in immune scores had the best prognosis. In contrast, S3 was poor in immune scores and had the worst prognosis. Subtype S1, S2, S3, and S4 were enriched in immune-related pathways, extracellular matrix-related pathways, metabolism-related pathways, and cancer-related pathways, respectively. Conclusion: The current study suggests that the immune subtypes based on gene expression profiles could contribute to select the appropriate MIBC patient for immunotherapies.

Background: The disease-associated cell lines used in the majority of preclinical trials should be first authenticated and identified to avoid directing research expenditure on wrong cells and obtaining irrelevant results. The present study evaluated the immunophenotypic and immunotypic authenticity of six human myeloma cell lines (HMCLs). Materials and Methods: Cytospin smear and Wright staining were used for invetigating cell morphology, the flowcytometry of the markers CD45, CD2, CD19, CD38 and CD138 for immunophenotypic investigations, capillary electrophoresis for the immunoglobulin secretion potency and immunofixation for the immunotypical investigation of the cells. Results: Given the definite plasma cell morphology, the identity of all the cell lines was confirmed, although a similar morphology was observed in L363 and JJN3. In addition to authenticating the myeloma nature of all the cell lines, immunophenotypic investigations suggested a complete similarity between L363 and JJN3 cell lines. Examining their immunotypes for a final confirmation found KMS12BM to be non-secretor, KMM1 to be BJP-λ and the remaining to be IgG-λ. Conclusion: Despite confirming the identity of four cell lines, i.e. RPMI-8226, KMS-12BM, KMM1 and LP1, that of JJN3 and L363 cells, whose immunotype was determined as IgGλ, was questioned owing to their fundamental morphological, immunophenotypic and immunotypic similarities. On the other hand, a reveiew of literature and ATCC.org suggested that the main nature of JJN3 is IgAκ. The authenticity of the JJN3 cell line was therefore unclear and it was indeed the same as that of L363. The JJN3 cell-line was therefore discarded, and the associated results were interpreted as consistent with the results of L363.

The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling. [Display omitted] • Development of a machine learning-based clinical immunoprofiling platform • Depiction of immune states by multiparameter flow cytometry and bulk RNA-seq using peripheral blood • Identification and validation of five immunotypes conserved across diverse diagnoses • Potential clinical utility in stratifying treatment responses via a simple blood test Dyikanov et al. developed a machine learning platform that uses a simple blood test to reveal cellular compositions reflective of a person's immune system. These compositions, delineated into five conserved immunotypes, can reflect a person's disease status or how someone responds to specific treatments, thus underscoring their potential clinical utility for cancer patients. [ABSTRACT FROM AUTHOR]

Immunotherapy, especially anti-PD-1, is becoming a pillar of modern muscle-invasive bladder cancer (MIBC) treatment. However, the objective response rates (ORR) are relatively low due to the lack of precise biomarkers to select patients. Herein, the molecular subtype, tumor mutation burden (TMB), and CD8+ T cells were calculated by the gene expression and mutation profiles of MIBC patients. MIBC immunotypes were constructed using clustering analysis based on tumor mutation burden, CD8+ T cells, and molecular subtypes. Mutated genes, enriched functional KEGG pathways and GO terms, and co-expressed network-specific hub genes have been identified. We demonstrated that ORR of immunotype A patients identified by molecular subtype, CD8+ T cells, and TMB is about 36% predictable. PIK3CA, RB1, FGFR3, KMT2C, MACF1, RYR2, and EP300 are differentially mutated among three immunotypes. Pathways such as ECM-receptor interaction, PI3K-Akt signaling pathway, and TGF-beta signaling pathway are top-ranked in enrichment analysis. Low expression of ACTA2 was associated with the MIBC survival benefit. The current study constructs a model that could identify suitable MIBC patients for immunotherapy, and it is an important step forward to the personalized treatment of bladder cancers. [ABSTRACT FROM AUTHOR]

Molecular classification of bladder cancer is becoming increasingly important for its clinical management. And, the current classifications are primarily based on gene expression profiles. We identified four immunotypes of bladder cancer (referred to as C1–C4) based on gene expression profiles performed by immune-related gene sets in three independent data sets, and proved that this classification is effective and reproducible. We found that C2 is an immune-infiltrating type and C4 is an immune “desert” type. These types are characterized by the up- and downregulation of genes encoding numerous immune checkpoint proteins and HLA and regulating human immune cell subgroups. The survival rate was better for the C2 subtype than for other subtypes. We believe that this can be explained by the antitumor effects of CD4 memory T cells and CD8 T cells as well as their ability to circumvent M0 macrophage antitumor immunity. In addition, C2 was most sensitive to not only anti-PD-1 immunosuppressive therapy, but also conventional chemotherapeutics such as gemcitabine and bleomycin. The C4 subtype was most sensitive to the chemotherapy drugs cisplatin and doxorubicin. This theoretical framework may guide the personalized treatment of bladder cancer in the future. It is worth noting that the C2 immune infiltration type positively correlates with a variety of stromal components, such as enrichment of endothelial cells and fibroblasts, epithelial-mesenchymal transition, and angiogenesis, together with enrichment of seven kinds of stem cells. We further identified tumor-related JAK-STAT and other signaling pathways in the C2 subtype, along with important mutations in the proteins involved in these pathways, revealing the complex mechanism underlying tumor immune escape. Our results, and particularly the identification of hub genes specific to the C2 and C4 subtypes, provide a reference for the development of immunotherapeutic agents against bladder cancer.

Molecular classification of bladder cancer is becoming increasingly important for its clinical management. And, the current classifications are primarily based on gene expression profiles. We identified four immunotypes of bladder cancer (referred to as C1–C4) based on gene expression profiles performed by immune-related gene sets in three independent data sets, and proved that this classification is effective and reproducible. We found that C2 is an immune-infiltrating type and C4 is an immune "desert" type. These types are characterized by the up- and downregulation of genes encoding numerous immune checkpoint proteins and HLA and regulating human immune cell subgroups. The survival rate was better for the C2 subtype than for other subtypes. We believe that this can be explained by the antitumor effects of CD4 memory T cells and CD8 T cells as well as their ability to circumvent M0 macrophage antitumor immunity. In addition, C2 was most sensitive to not only anti-PD-1 immunosuppressive therapy, but also conventional chemotherapeutics such as gemcitabine and bleomycin. The C4 subtype was most sensitive to the chemotherapy drugs cisplatin and doxorubicin. This theoretical framework may guide the personalized treatment of bladder cancer in the future. It is worth noting that the C2 immune infiltration type positively correlates with a variety of stromal components, such as enrichment of endothelial cells and fibroblasts, epithelial-mesenchymal transition, and angiogenesis, together with enrichment of seven kinds of stem cells. We further identified tumor-related JAK-STAT and other signaling pathways in the C2 subtype, along with important mutations in the proteins involved in these pathways, revealing the complex mechanism underlying tumor immune escape. Our results, and particularly the identification of hub genes specific to the C2 and C4 subtypes, provide a reference for the development of immunotherapeutic agents against bladder cancer. [ABSTRACT FROM AUTHOR]

Background: The disease-associated cell lines used in the majority of preclinical trials should be first authenticated and identified to avoid directing research expenditure on wrong cells and obtaining irrelevant results. The present study evaluated the immunophenotypic and immunotypic authenticity of six human myeloma cell lines (HMCLs). Materials and Methods: Cytospin smear and Wright staining were used for invetigating cell morphology, the flowcytometry of the markers CD45, CD2, CD19, CD38 and CD138 for immunophenotypic investigations, capillary electrophoresis for the immunoglobulin secretion potency and immunofixation for the immunotypical investigation of the cells. Results: Given the definite plasma cell morphology, the identity of all the cell lines was confirmed, although a similar morphology was observed in L363 and JJN3. In addition to authenticating the myeloma nature of all the cell lines, immunophenotypic investigations suggested a complete similarity between L363 and JJN3 cell lines. Examining their immunotypes for a final confirmation found KMS12BM to be non-secretor, KMM1 to be BJP-λ and the remaining to be IgG-λ. Conclusion: Despite confirming the identity of four cell lines, i.e. RPMI-8226, KMS-12BM, KMM1 and LP1, that of JJN3 and L363 cells, whose immunotype was determined as IgGλ, was questioned owing to their fundamental morphological, immunophenotypic and immunotypic similarities. On the other hand, a reveiew of literature and ATCC.org suggested that the main nature of JJN3 is IgAκ. The authenticity of the JJN3 cell line was therefore unclear and it was indeed the same as that of L363. The JJN3 cell-line was therefore discarded, and the associated results were interpreted as consistent with the results of L363. [ABSTRACT FROM AUTHOR]

Background: In this study, effective antigens of mRNA vaccine were excavated from the perspective of ICD, and ICD subtypes of PRAD were further distinguished to establish an ICD landscape, thereby determining suitable vaccine recipients., Research Design and Methods: TCGA and MSKCC databases were applied to acquire RNA-seq data and corresponding clinical data of 554 and 131 patients, respectively. GEPIA was employed to measure prognostic indices. Then, a comparison of genetic alterations was performed utilizing cBioPortal, and correlation of identified ICD antigens with immune infiltrating cells was analyzed employing TIMER. Moreover, ICD subtypes were identified by means of consensus cluster, and ICD landscape of PRAD was depicted utilizing graph learning-based dimensional reduction., Results: In total, 4 PRAD antigens were identified in PRAD, including FUS, LMNB2, RNPC3, and ZNF700, which had association with adverse prognosis and infiltration of APCs. PRAD patients were classified as two ICD subtypes based on their differences in molecular, cellular, and clinical features. Furthermore, ICD modulators and immune checkpoints were also differentially expressed between two ICD subtype tumors. Finally, the ICD landscape of PRAD showed substantial heterogeneity among individual patients., Conclusions: In summary, the research may provide a theoretical foundation for developing mRNA vaccine against PRAD as well as determining appropriate vaccine recipients.

Immune-cell infiltration is associated with improved survival in melanoma. Human melanoma metastases may be grouped into immunotypes representing patterns of immune-cell infiltration: A (sparse), B (perivascular cuffing), and C (diffuse). Immunotypes have not been defined for murine melanomas, but may provide opportunities to understand mechanism-driving immunotype differences. We performed immunohistochemistry with immune-cell enumeration, immunotyping, and vascular density scoring in genetically engineered (Braf/Pten and Braf/Pten/β-catenin) and transplantable (B16-F1, B16-OVA, and B16-AAD) murine melanomas. The transplantable tumors were grown in subcutaneous (s.c.) or intraperitoneal (i.p.) locations. Braf/Pten and Braf/Pten/β-catenin tumors had low immune-cell densities, defining them as Immunotype A, as did B16-F1 tumors. B16-OVA (s.c. and i.p.) and B16-AAD s.c. tumors were Immunotype B, while B16-AAD i.p. tumors were primarily Immunotype C. Interestingly, the i.p. location was characterized by higher immune-cell counts in B16-OVA tumors, with counts that trended higher for B16-F1 and B16-AAD. The i.p. location was also characterized by higher vascularity in B16-F1 and B16-AAD tumors. These findings demonstrate that spontaneously mutated neoantigens in B16 melanomas were insufficient to induce robust intratumoral immune-cell infiltrates, but instead were Immunotype A tumors. The addition of model neoantigens (OVA or AAD) to B16 enhanced infiltration, but this most often resulted in Immunotype B. We find that tumor location may be an important element in enabling Immunotype C tumors. In aggregate, these data suggest important roles both for the antigen type and for the tumor location in defining immunotypes. [ABSTRACT FROM AUTHOR]

Background: mRNA vaccines have been investigated in multiple tumors, but limited studies have been conducted on their use for hepatocellular carcinoma (HCC)., Aim: To identify candidate mRNA vaccine antigens for HCC and suitable subpopulations for mRNA vaccination., Methods: Gene expression profiles and clinical information of HCC datasets were obtained from International Cancer Genome Consortium and The Cancer Genome Atlas. Genes with somatic mutations and copy number variations were identified by cBioPortal analysis. The differentially expressed genes with significant prognostic value were identified by Gene Expression Profiling Interactive Analysis 2 website analysis. The Tumor Immune Estimation Resource database was used to assess the correlation between candidate antigens and the abundance of antigen-presenting cells (APCs). Tumor-associated antigens were overexpressed in tumors and associated with prognosis, genomic alterations, and APC infiltration. A consensus cluster analysis was performed with the Consensus Cluster Plus package to identify the immune subtypes. The weighted gene coexpression network analysis (WGCNA) was used to determine the candidate biomarker molecules for appropriate populations for mRNA vaccines., Results: AURKA, CCNB1, CDC25C, CDK1, TRIP13, PES1, MCM3, PPM1G, NEK2, KIF2C, PTTG1, KPNA2 , and PRC1 were identified as candidate HCC antigens for mRNA vaccine development. Four immune subtypes (IS1-IS4) and five immune gene modules of HCC were identified that were consistent in both patient cohorts. The immune subtypes showed distinct cellular and clinical characteristics. The IS1 and IS3 immune subtypes were immunologically "cold". The IS2 and IS4 immune subtypes were immunologically "hot", and the immune checkpoint genes and immunogenic cell death genes were upregulated in these subtypes. IS1-related modules were identified with the WGCNA algorithm. Ultimately, five hub genes ( RBP4, KNG1, METTL7A, F12, and ABAT ) were identified, and they might be potential biomarkers for mRNA vaccines., Conclusion: AURKA, CCNB1, CDC25C, CDK1, TRIP13, PES1, MCM3, PPM1G, NEK2, KIF2C, PTTG1, KPNA2 , and PRC1 have been identified as candidate HCC antigens for mRNA vaccine development. The IS1 and IS3 immune subtypes are suitable populations for mRNA vaccination. RBP4, KNG1, METTL7A, F12, and ABAT are potential biomarkers for mRNA vaccines., Competing Interests: Conflict-of-interest statement: The authors declare no conflict of interest for this article., (©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.)

[Display omitted] Despite similar clinical symptoms, peanut-allergic (PA) individuals may respond quite differently to the same therapeutic interventions. This study aimed to determine whether inherent qualities of cell response at baseline could influence response to peanut oral immunotherapy (PnOIT). We first performed ex vivo T-cell profiling on peanut-reactive CD154+CD137+ T (pTeff) cells from 90 challenge-confirmed PA individuals. We developed a gating strategy for unbiased assessment of the phenotypic distribution of rare pTeff cells across different memory CD4+ T-cell subsets to define patient immunotype. In longitudinal samples of 29 PA participants enrolled onto the IMPACT trial of PnOIT, we determined whether patient immunotype at baseline could influence response to PnOIT. Our data emphasize the heterogeneity of pTeff cell responses in PA participants with 2 mutually exclusive phenotypic entities (CCR6−CRT H 2+ and CCR6+CRT H 2−). Our findings lead us to propose that peanut allergy can be classified broadly into at least 2 discrete subtypes, termed immunotypes, with distinct immunologic and clinical characteristics that are based on the proportion of T H 2A pTeff cells. PnOIT induced elimination of T H 2A pTeff cells in the context of the IMPACT clinical trial. Only 1 PA patient with a low level of T H 2A pTeff cells at baseline experienced long-lasting benefit of remission after PnOIT discontinuation. Dividing PA patients according to their individual peanut-specific T-cell profile may facilitate patient stratification in clinical settings by identifying which immunotypes might respond best to different therapies. [ABSTRACT FROM AUTHOR]

Background: Although mRNA vaccines have been effective against multiple cancers, their efficacy against stomach adenocarcinoma (STAD) remains undefined. Immunotyping can indicate the comprehensive immune status in tumors and their immune microenvironment, which is closely associated with therapeutic response and vaccination potential. The aim of this study was to identify potential antigens in STAD for mRNA vaccine development, and further distinguish immune subtypes of STAD to construct an immune landscape for selecting suitable patients for vaccination. Methods: The gene expression and clinicopathological features of patients with gastric cancer were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Program (GTEx). 729 samples from GSE66229 and GSE84437 were downloaded through GEO and were used as the validation cohorts. Differential gene expression, genetic alterations and prognosis were analyzed using the R package, cBioPortal program and Kaplan-Meier. The relationship between tumor antigens and immune cells was evaluated and plotted by TIMER. ConsensusClusterPlus was used for consistency matrix construction and data clustering, and graph learning-based dimensional reduction was used to depict immune landscape. WGCNA was used to estimate the relationship between the color modules and immune subtypes. Results: Two overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in STAD, including RAI14 and NREP. The immune subtypes showed distinct molecular, cellular and clinical characteristics. IS1 and IS2 exhibited immune-activated phenotypes and correlated to better survival compared to IS3, while IS3 tumors was immunologically cold. Immunogenic cell death modulators, immune checkpoints, and CA125, and CEA were also differentially expressed among the three immune subtypes. Finally, the immune landscape of STAD showed a high degree of heterogeneity between individual patients. Conclusion: RAI14 and NREP are potential antigens for developing anti-STAD mRNA vaccine, and patients with IS1 and IS3 tumors may be suitable for vaccination., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wei, Sun, Chen, Li and Hu.)

Background: Clear cell renal cell carcinoma (ccRCC) is a highly immunogenic tumor. The purpose of the present study was to establish a novel immunotype for different immune infiltration and overall survival (OS) of patients with ccRCC., Methods: Based on the Cancer Genome Atlas Project (TCGA) database (discovery set), a novel immunotype was established using ssGSEA methods. The databases of Fudan University Shanghai Cancer Center (FUSCC) and Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine (XHH) served as an external validation set. GSEA was carried out to identify the immunotype associated signal transduction pathways., Results: A total of 652 ccRCC patients were included in our study. We constructed a novel immunotype of ccRCC to classify patients into three groups: high-immunity, moderate-immunity, and low-immunity. The high-immunity and moderate-immunity groups had higher ImmuneScores, ESTIMATEScores, StromalScores, and lower tumor purity than that of the low-immunity group in both sets. Additionally, the patients from the high-immunity and moderate-immunity groups had longer survival than patients from low-immunity group in both discovery set and validation set (HR = 2.54, 95% CI: 1.56-4.13, p < 0.01; HR = 2.75, 95% CI: 1.24-6.11, p = 0.01)., Conclusion: In summary, we defined a novel immunotype of ccRCC. The immune types could be used as a clinical predictive tool to identify ccRCC patients with different survival. In addition, the immune-related biological signaling pathway also brought new insights on the mechanism of ccRCC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yu, Zhang, Gao, Qian, Tang and Shao.)

Neisseria meningitidis shows great variation in expression of structurally different lipooligosaccharides (LOS) on its cell surface. To better understand the LOS diversity that may occur within an individual strain, a group C wild-type strain, BB305-Tr4, and two stable isogenic LOS variants, Tr5 and Tr7, were selected for this study. SDS–PAGE analysis showed a size reduction of Tr5 and Tr7 LOS compared to that of Tr4. Immunoblotting showed that parental Tr4 LOS reacted with L1, L2 and L3,7 antibodies, variant Tr5 LOS with L1 and L6 antibodies, while Tr7 LOS was non-typeable. Genetic analysis showed that the gene organization at the lgt-1 locus in the three strains was lgtZ,C,A,B,H4 in Tr4, lgtZ,C,A,H4 in Tr5 and lgtZ,C,A,H9 in Tr7. The genetic differences in the three strains were consistent with their phenotypic changes. Sequence comparison revealed two independent recombination events. The first was the recombination of repeated DNA fragments in the flanking regions to delete lgtB in Tr5. The second was the recombination of a fragment of two genes, lgtB and lgtH4, to create an inactive lgtH9 allele with a mosaic structure in Tr7. These findings suggest that besides phase variation, homologous recombination can contribute to the genetic diversity of the lgt locus and to the generation of LOS variation in N. meningitidis. [Copyright &y& Elsevier]

Background: Immunotherapies including PD-1/PD-L1 antibodies have been approved for the treatment of Muscle-invasive Bladder Cancer (MIBC) patients. However, immunotherapies could only be beneficial for about 20% MIBC patients. Thus, identification of the immune subtype is becoming increasingly important. This study aimed to explore the immune subtype by analyzing the gene expression profiles., Methods: A total of 6 datasets including (GSE13507, GSE31684, GSE32548, GSE32894, GSE69795, and TCGA-BLCA) were downloaded. The gene expression profiles from different datasets were combined since the batch effects were removed. We performed unsupervised clustering analysis to identify the immune subtype by the combined gene expression profiles. The tumor-infiltration levels of 22 immune cells, immune scores, and tumor purity were calculated, and the survival analysis was performed to investigate the prognosis difference between immune subtypes. The enriched pathways for each immune subtype were obtained., Results: We identified four novel immune subtypes (referred to S1, S2, S3, and S4) among MIBC patients. We found that S1 was enriched in immune scores had the best prognosis. In contrast, S3 was poor in immune scores and had the worst prognosis. Subtype S1, S2, S3, and S4 were enriched in immune-related pathways, extracellular matrix-related pathways, metabolism-related pathways, and cancer-related pathways, respectively., Conclusion: The current study suggests that the immune subtypes based on gene expression profiles could contribute to select the appropriate MIBC patient for immunotherapies.

Background: Microsatellite instability (MSI) remains a focus of interest in cancer research, but the characteristics of MSI in gastric cancer (GC) are ambiguous., Methods: In this retrospective study, we analyzed the prevalence of MSI and the expression of programmed death-ligand 1 (PD-L1) and cluster of differentiation 8 (CD8) cells in Chinese GC patients. A total of 393 GC patients admitted to two centers from January 2010 to December 2017 were enrolled., Results: The prevalence of MSI in this cohort was 3.4% and most frequently occurred in females, patients aged between 59 and 69 years, and patients at a lower clinical stage. All MSI GCs had CD8 expression but lacked PD-L1 expression, indicating that MSI was related to CD8 expression but irrelevant to PD-L1 expression. However, there was no significant difference in the expression of CD8/PD-L1 between MSI GC and microsatellite stable (MSS) GC. Kaplan-Meier survival curves revealed that patients with MSI had a significantly longer overall survival (OS) than patients with MSS., Conclusions: In Chinese GC patients, MSI frequently occurred in females, patients aged between 59 and 69, and patients with lower clinical stages. Patients with MSI-High (MSI-H) and MSI-Low (MSI-L) had a longer OS than patients with MSS. MSI was related to CD8 expression but irrelevant to PD-L1 expression., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jgo-21-695). All authors acknowledge that this work received technical support from Shanghai Tongshu Biotechnology Co. Ltd. Chunxiao Wang is from Shanghai Tongshu Biotechnology Co. Ltd. The authors have no other conflicts of interest to declare., (2021 Journal of Gastrointestinal Oncology. All rights reserved.)

Background and Aims : The tumor microenvironment can be divided into inflamed, immune-excluded and immune - desert phenotypes according to CD8 + T cell categories with differential programmed cell death protein 1 (PD-L1) expression. The study aims to construct a novel immunotype-based risk stratification model to predict postsurgical survival and adjuvant trans-arterial chemoembolization (TACE) response in patients with hepatocellular carcinoma (HCC). Methods: A total of 220 eligible HCC patients participated in this study. CD8 + T cell infiltration and PD-L1 expression mode were estimated by immunohistochemical staining. A risk stratification model was developed and virtualized by a nomogram that integrated these independent prognostic factors. The postoperative prognosis and adjuvant TACE benefits were evaluated with a novel immunotype-based risk stratification model. Results: A total of 220 patients were finally identified. Immune-desert, immune-excluded, and inflamed immunotypes represented 45%, 24%, and 31% of HCC, respectively. Univariate and multivariate analyses identified immunotype and PD-L1 expression mode as independent prognostic factors for overall survival time (OS) and recurrence-free survival time (RFS). The nomogram was constructed by integrating immunotype, PD-L1 expression, Barcelona Clinic Liver Cancer (BCLC) stage and tumor grade. The C-index was 0.794 in the training cohort and 0.813 in the validation cohort. A risk stratification system was constructed based on the nomogram classifying HCC patients into 3 risk groups. The average OS times in the low-risk, intermediate-risk and high-risk groups in all cohorts were 77.1 months (95% CI 71.4-82.9), 53.7 months (95% CI 48.2-59.2), and 25.6 months (95% CI 21.4-29.7), respectively. Further analysis showed that OS was significantly improved by adjuvant TACE in the low- and intermediate-risk groups ( P= 0.041 and P =0.010, respectively) but not in the high-risk group ( P =0.398). Conclusion: A novel immunotype-based risk stratification model was built to predict postoperative prognosis and adjuvant TACE benefit in HCC patients. These tools can assist in building a more customized method of HCC treatment., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

The article offers information on the intensive care unit (ICU) patients suffering from Acute respiratory distress syndrome (ARDS). It mentions that these patients suffer high mortality rates and often undergo mechanical ventilation in the ICU. The article discusses a study published in the issue regarding the analysis of alveolar macrophages polarization in ARDS.

Background: Stratification of tumors is necessary to achieve better clinical outcomes. Hepatocellular carcinoma (HCC) is commonly associated with mutation of the TP53 gene and heterogeneity in immune cell content. However, TP53 mutation-associated immunotype of HCC has not been reported yet. This study aimed to identify the TP53 mutation-associated immunotype in HCC., Methods: The mutation annotation format (MAF) document, mRNA expression data, and clinical data of HCC patients were downloaded from the publicly available The Cancer Genome Atlas (TCGA) data portal. Data from 332 HCC patients were analyzed in this study. Infiltrating immune cells were evaluated by the well-known CIBERSORT method. Additional mutation data of HCC patients were downloaded from the Catalogue of Somatic Mutations in Cancer (COSMIC) database., Results: The TP53 gene harbored the highest frequency of mutations in HCC patients. Consequently, five lethal features, including TP53 mutations, were screened by least absolute shrinkage and selector operation (LASSO)-COX regression, according to TP53 mutations and 22 infiltrating immune cells. Two distinct subgroups of HCC were identified, namely, immunotypes A and B. Furthermore, the expression levels of co-inhibitory immune checkpoints were significantly upregulated, and the gene ontology (GO) terms or pathways to boost immune responses were found to be inhibited in the immunotype B subgroup compared to that in the immunotype A subgroup. Finally, we proved immunotype to be an independent adverse prognostic factor that contributed to improvement in the predictive accuracy of the immunotype-based model and helped in avoiding excessive medical treatment., Conclusions: Two distinct immunotypes of HCC, in terms of prognosis, phenotype, and function, were identified and the traditional understanding of intratumoralCD8 + T cells was subverted. Moreover, the identified immunotypes contributed to improving the predictive accuracy of the immunotype-based model and helped in avoiding excessive medical treatment in some HCC patients., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare., (2020 Annals of Translational Medicine. All rights reserved.)