Comprehensive Analyses of Immune Subtypes of Stomach Adenocarcinoma for mRNA Vaccination

Structural insights into the dual Ca2+-sensor-mediated activation of the PPEF phosphatase family

Serine/threonine-protein phosphatases with EF-hands (PPEFs) are a family of highly conserved proteins implicated in cancer and neuronal degeneration. The initially characterized member, Drosophila melanogaster retinal degeneration C (RDGC) contains a calmodulin (CaM)-interacting extended-IQ motif and a Ca2+-binding EF-like/EF-hand tandem. However, the molecular regulation of PPEF is poorly understood. In this study, we use cryogenic-electron microscopy to delineate the structures of the RDGC/CaM holoenzyme. In the absence of Ca2+, CaM and the EF-like/EF-hand tandem allow the extended-IQ motif to block substrate access to the catalytic sites, constituting an auto-inhibitory mechanism. Upon Ca2+ binding, CaM and the EF-like/EF-hand tandem drive drastic conformational changes in the extended-IQ motif to unlock the catalytic sites. This dual Ca2+-sensor-mediated activation is evolutionarily conserved in mammals. This study provides mechanistic insight into the molecular activation of PPEFs, paving the way for the development of therapeutic strategies for PPEF-related human diseases.

Mannan-Decorated Lipid Calcium Phosphate Nanoparticle Vaccine Increased the Antitumor Immune Response by Modulating the Tumor Microenvironment

With the rapid development of tumor immunotherapy, nanoparticle vaccines have attracted much attention as potential therapeutic strategies. A systematic review and analysis must be carried out to investigate the effect of mannose modification on the immune response to nanoparticles in regulating the tumor microenvironment, as well as to explore its potential clinical application in tumor therapy. Despite the potential advantages of nanoparticle vaccines in immunotherapy, achieving an effective immune response in the tumor microenvironment remains a challenge. Tumor immune escape and the overexpression of immunosuppressive factors limit its clinical application. Therefore, our review explored how to intervene in the immunosuppressive mechanism in the tumor microenvironment through the use of mannan-decorated lipid calcium phosphate nanoparticle vaccines to improve the efficacy of immunotherapy in patients with tumors and to provide new ideas and strategies for the field of tumor therapy.

KLF4 Induces Colorectal Cancer by Promoting EMT via STAT3 Activation

OBJECTIVE

Krüppel-like factor 4 (KLF4) has been demonstrated to exert a pro-carcinogenic effect in solid tissues. However, the precise biological function and underlying mechanisms in colorectal cancer (CRC) remains elucidated.

AIMS

To investigate whether KLF4 participates in the proliferation and invasion of CRC.

METHODS

The expression of KLF4 was investigated using immunohistochemistry and immunoblotting. The clinical significance of KLF4 was evaluated. Furthermore, the effect of inhibiting or overexpressing KLF4 on tumor was examined. Immunoblotting and qPCR were used to detect Epithelial-mesenchymal transition-related proteins levels. Additionally, the molecular function of KLF4 is related to the STAT3 signaling pathway and was determined through JASPAR, GSEA analysis, and in vitro experiments.

RESULTS

KLF4 exhibits down-regulated expression in CRC and is part of the vessel invasion, TNM stage, and worse prognosis. In vitro studies have shown that KLF4 promotes cellular proliferation and invasion, as well as EMT processes. Xenograft tumor models confirmed the oncogenic role of KLF4 in nude mice. Furthermore, GSEA and JASPAR databases analysis reveal that the binding of KLF4 to the signal transducer and activator of transcription 3 (STAT3) promoter site induces activation of p-STAT3 signaling. Subsequent targeting of STAT3 confirmed its pivotal role in mediating the oncogenic effects exerted by KLF4.

CONCLUSION

The study suggests that KLF4 activates STAT3 signaling, inducing epithelial-mesenchymal transition, thereby promoting CRC progression.

Integrated single-cell sequencing, spatial transcriptome sequencing and bulk RNA sequencing highlights the molecular characteristics of parthanatos in gastric cancer

BACKGROUND

Parthanatos is a novel programmatic form of cell death based on DNA damage and PARP-1 dependency. Nevertheless, its specific role in the context of gastric cancer (GC) remains uncertain.

METHODS

In this study, we integrated multi-omics algorithms to investigate the molecular characteristics of parthanatos in GC. A series of bioinformatics algorithms were utilized to explore clinical heterogeneity of GC and further predict the clinical outcomes.

RESULTS

Firstly, we conducted a comprehensive analysis of the omics features of parthanatos in various human tumors, including genomic mutations, transcriptome expression, and prognostic relevance. We successfully identified 7 cell types within the GC microenvironment: myeloid cell, epithelial cell, T cell, stromal cell, proliferative cell, B cell, and NK cell. When compared to adjacent non-tumor tissues, single-cell sequencing results from GC tissues revealed elevated scores for the parthanatos pathway across multiple cell types. Spatial transcriptomics, for the first time, unveiled the spatial distribution characteristics of parthanatos signaling. GC patients with different parthanatos signals often exhibited distinct immune microenvironment and metabolic reprogramming features, leading to different clinical outcomes. The integration of parthanatos signaling and clinical indicators enabled the creation of novel survival curves that accurately assess patients' survival times and statuses.

CONCLUSIONS

In this study, the molecular characteristics of parthanatos' unicellular and spatial transcriptomics in GC were revealed for the first time. Our model based on parthanatos signals can be used to distinguish individual heterogeneity and predict clinical outcomes in patients with GC.

Identification of tumor antigens and immune subtypes of hepatocellular carcinoma for mRNA vaccine development

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.

Comprehensive analysis of immune subtypes reveals the prognostic value of cytotoxicity and FAP+ fibroblasts in stomach adenocarcinoma

BACKGROUND

The heterogeneity limits the effective application of immune checkpoint inhibitors for patients with stomach adenocarcinoma (STAD). Precise immunotyping can help select people who may benefit from immunotherapy and guide postoperative management by describing the characteristics of tumor microenvironment.

METHODS

Gene expression profiles and clinical information of patients were collected from ACRG and TCGA-STAD datasets. The immune subtypes (ISs) were identified by consensus clustering analysis. The tumor immune microenvironments (TIME) of each IS were characterized using a series of immunogenomics methods and further confirmed by multiplex immunohistochemistry (mIHC) staining in clinical samples. Two online datasets and one in-house dataset were utilized to construct and validate a prognostic immune-related gene (IRG) signature.

RESULTS

STAD patients were stratified into five reproducible ISs. IS1 (immune deserve subtype) had low immune infiltration and the highest degree of HER2 gene mutation. With abundant CD8+ T cells infiltration and activated cytotoxicity reaction, patients in the IS2 (immune-activated subtype) had the best overall survival (OS). IS3 and IS4 subtypes were both in the reactive stroma state and indicated the worst prognosis. However, IS3 (immune-inhibited subtype) was characterized by enrichment of FAP+ fibroblasts and upregulated TGF-β signaling pathway, while IS4 (activated stroma subtype) was characterized by enrichment of ACTA2+ fibroblasts. In addition, mIHC staining confirmed that TGF-β upregulated FAP+ fibroblasts were independent risk factor of OS. IS5 (chronic inflammation subtype) displayed moderate immune cells infiltration and had a relatively good survival. Lastly, we developed a nine-IRG signature model with a robust performance on overall survival prognostication.

CONCLUSIONS

The immunotyping is indicative for characterize the TIME heterogeneity and the prediction of tumor prognosis for STADs, which may provide valuable stratification for the design of future immunotherapy.

mRNA-From COVID-19 Treatment to Cancer Immunotherapy

This review provides an overview covering mRNA from its use in the COVID-19 pandemic to cancer immunotherapy, starting from the selection of appropriate antigens, tumor-associated and tumor-specific antigens, neoantigens, the basics of optimizing the mRNA molecule in terms of stability, efficacy, and tolerability, choosing the best formulation and the optimal route of administration, to summarizing current clinical trials of mRNA vaccines in tumor therapy.

STRA6 regulates tumor immune microenvironment and is a prognostic marker in BRAF-mutant papillary thyroid carcinoma

BACKGROUND

BRAF mutation is one of the most common genetic alterations contributing to the initiation and progression of papillary thyroid carcinoma (PTC). However, the prognostic value of BRAF mutation for PTC is limited. Novel markers are needed to identify BRAF-mutant patients with poor prognosis.

METHODS

Transcriptional expression data were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Pathway enrichment was performed by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and gene set enrichment analysis (GSEA). Protein-protein interaction networks were predicted by the GeneMANIA. The correlation between STRA6 expression and immune infiltration was analyzed by tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB). Immunohistochemistry was used to detect the STRA6 protein expression level of PTC. Infiltration of regulatory T cells (Tregs) and CD8+ T cells in tumor samples were analyzed by fluorescent multiplex immunohistochemistry.

RESULTS

In BRAF-mutant PTC, STRA6 was extremely upregulated and predicted unfavorable survival, which was an independent risk factor for increased mortality risk. Bioinformatic analyses indicated that STRA6 might activate the MAPK pathway synergistically with BRAF^V600E. The expression of STRA6 was associated with immune infiltrates and T cell exhaustion. Fluorescent multiplex immunohistochemistry showed that STRA6 increased Tregs abundance and decreased CD8+ T cells infiltration in PTC. Moreover, STRA6 promoted epithelial-mesenchymal transition via increased cancer-associated fibroblasts infiltration.

CONCLUSIONS

Our study demonstrates STRA6 may serve as a prognostic marker for BRAF-mutated PTC, which may drive thyroid carcinogenesis via activation of oncogenic pathway and regulation of tumor immunosuppressive microenvironment.

Bioinformatics analyses for the identification of tumor antigens and immune subtypes of gastric adenocarcinoma

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.