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Identification of characteristic markers correlated with Th2 cell infiltration and metabolism molecular subtype in pancreatic adenocarcinoma.
BACKGROUND: Pancreatic adenocarcinoma, the deadliest malignant cancer, has gradually become the third leading cause of cancer-related death. Multidisciplinary therapy has been difficult to implement because of the particularity of pancreatic adenocarcinoma. Research has increasingly indicated the significance of metabolic adaption in pancreatic adenocarcinoma. The difference in metabolism may influence immune cell infiltration in pancreatic adenocarcinoma. Novel immune-related metabolism biomarkers are needed to improve the therapeutic outcomes of existing targeted therapies. METHODS: We enrolled whole-genome sequencing data and clinical information about 168 pancreatic adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database, other pancreatic adenocarcinoma samples, and clinical information from other cohorts. We used the gene set variation analysis (GSVA) package to calculate feature score, the weighted gene co-expression network analysis (WGCNA) and randomSurvivalForest package to screen hub genes, the ConsenClusterPlus package to classify subtypes, the pRRopthetic package to evaluate drug sensibility, the maftools package to analyze mutation information and the Seurat package to analyze single cell sequencing data. RESULTS: We revealed the prognosis significance of Th2 cell infiltration, classified two subtypes based on hub genes, compared immune cell infiltration, substance metabolism, cellular processes, gene mutation, and copy number variation (CNV) between subtypes and explored the clinical and biological features of Th2 cell infiltration. CONCLUSIONS: We displayed the poor prognosis significance of Th2 cell infiltration and the significant difference of simple nucleotide polymorphism, CNV, natural killer (NK) CD56 bright cell infiltration, substance metabolism, autophagy and necroptosis between subtypes. Additionally, we discovered the sensitivity difference of chemotherapy drug and the Th2 cell infiltration changes after chimeric antigen receptor T cells (CAR-T) cell therapy and radiotherapy and explored the differences between normal liver and metastatic liver tissues of pancreatic adenocarcinoma patients.
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Diversity of ribosomes at the level of rRNA variation associated with human health and disease.
Ribosomal DNA and RNA (rDNA and rRNA) sequences are usually discarded from sequencing analyses. But with hundreds of copies of rDNA genes it is unknown whether they possess sequence variations that form different types of ribosomes that affect human physiology and disease. Here, we developed an algorithm for variant-calling between paralog genes (termed RGA) and compared rDNA variations found in short- and long-read sequencing data from the 1,000 Genomes Project (1KGP) and Genome In A Bottle (GIAB). We additionally developed a novel protocol for long-read sequencing full-length rRNA (RIBO-RT) from actively translating ribosomes. Our analyses identified hundreds of rDNA variants, most of which, surprisingly, are short insertion-deletions (indels) and dozens of highly abundant rRNA variants that are incorporated into translationally active ribosomes. To visualize variant ribosomes at the single cell level, we developed an in-situ rRNA sequencing method (SWITCH-seq) which revealed that variants are co-expressed within individual cells. Strikingly, by analyzing rDNA, we found that variants assemble into distinct ribosome subtypes. We discovered that these subtypes acquire different rRNA structures by successfully employing dimethyl sulfate (DMS) probing of full length rRNA. With this atlas we investigated rRNA variation changes across human tissues and cancer types. This revealed tissue-specific rRNA subtype expression in endoderm/ectoderm-derived tissues. In cancer, low abundant rRNA variants can become highly expressed, which suggests the presence of cancer-specific ribosomes. Together, this study identifies and comprehensively characterizes the diversity of ribosomes at the level of rRNA variants which is dominated by indel variants, their chromosomal location and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.
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Expression Analysis and Significance of PD-1, LAG-3, and TIM-3 in Human Non-Small Cell Lung Cancer Using Spatially Resolved and Multiparametric Single-Cell Analysis.
PURPOSE: To determine the tumor tissue/cell distribution, functional associations, and clinical significance of PD-1, LAG-3, and TIM-3 protein expression in human non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: Using multiplexed quantitative immunofluorescence, we performed localized measurements of CD3, PD-1, LAG-3, and TIM-3 protein in >800 clinically annotated NSCLCs from three independent cohorts represented in tissue microarrays. Associations between the marker's expression and major genomic alterations were studied in The Cancer Genome Atlas NSCLC dataset. Using mass cytometry (CyTOF) analysis of leukocytes collected from 20 resected NSCLCs, we determined the levels, coexpression, and functional profile of PD-1, LAG-3, and TIM-3 expressing immune cells. Finally, we measured the markers in baseline samples from 90 patients with advanced NSCLC treated with PD-1 axis blockers and known response to treatment. RESULTS: PD-1, LAG-3, and TIM-3 were detected in tumor-infiltrating lymphocytes (TIL) from 55%, 41.5%, and 25.3% of NSCLC cases, respectively. These markers showed a prominent association with each other and limited association with major clinicopathologic variables and survival in patients not receiving immunotherapy. Expression of the markers was lower in EGFR-mutated adenocarcinomas and displayed limited association with tumor mutational burden. In single-cell CyTOF analysis, PD-1 and LAG-3 were predominantly localized on T-cell subsets/NKT cells, whereas TIM-3 expression was higher in NK cells and macrophages. Coexpression of PD-1, LAG-3, and TIM-3 was associated with prominent T-cell activation (CD69/CD137), effector function (Granzyme-B), and proliferation (Ki-67), but also with elevated levels of proapoptotic markers (FAS/BIM). LAG-3 and TIM-3 were present in TIL subsets lacking PD-1 expression and showed a distinct functional profile. In baseline samples from 90 patients with advanced NSCLC treated with PD-1 axis blockers, elevated LAG-3 was significantly associated with shorter progression-free survival. CONCLUSIONS: PD-1, LAG-3, and TIM-3 have distinct tissue/cell distribution, functional implications, and genomic correlates in human NSCLC. Expression of these immune inhibitory receptors in TILs is associated with prominent activation, but also with a proapoptotic T-cell phenotype. Elevated LAG-3 expression is associated with insensitivity to PD-1 axis blockade, suggesting independence of these immune evasion pathways.
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Identification of cancer-associated fibroblast subpopulation and construction of an immunotherapy signature for gastric cancer.
BACKGROUND: Cancer-associated fibroblasts (CAFs) are thought to contribute to malignant tumor progression. Although it has been reported that signatures based on CAFs-specific genes could be used to evaluate the prognosis of gastric cancer (GC), as a heterogeneous subgroup, the CAFs subpopulations and their characteristics in the GC microenvironment were still ambiguous. This study aimed to identify CAFs subgroups in GC and evaluate their prognostic and immunotherapy relevance. METHODS: We utilized the Gene Expression Omnibus (GEO) database to acquire single-cell sequencing data of CAFs associated with GC, and The Cancer Genome Atlas (TCGA) database to obtain GC patient messenger RNA (mRNA) expression profiles. All CAFs were classified using unsupervised clustering based on the expression of 235 characteristic genes. The unsupervised clustering results indicated that the CAFs in the GC microenvironment were divided into four clusters. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed the intrinsic differences of these clusters and the CIBERSORT algorithm was used to perform immune cell infiltration analysis. RESULTS: Cluster1, Cluster2 and Cluster4 were partly related to extracellular matrix production, while Cluster3 was mainly related to the TGF-β pathway. In addition, the CAF-related score based on Cluster3 (CRS3) could significantly distinguish the prognosis of patients. Moreover, patients with low CRS3 scores had a higher tumor mutation burden and higher levels of immune checkpoints (CTLA-4, LAG3, MAGE-A3, PD-1 and PD-L1), which might indicate a higher immunotherapy response. CONCLUSIONS: All in all, our study revealed four heterogeneous subpopulations of CAFs in the GC microenvironment, and highlighted that Cluster3 was associated with prognosis and response to immunotherapy.
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Programmed Cell Death 10 (PDCD10) Is a Candidate Tumor-associated Gene in Esophageal Squamous Cell Carcinoma.
BACKGROUND/AIM: Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy with poor survival rates. Effective molecular-targeted therapies are urgently needed. This study aimed to identify novel candidate tumor-associated genes in ESCC by analyzing chromosomal amplification regions. MATERIALS AND METHODS: DNA copy number variation (CNV) and mRNA expression data were obtained from The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). Single-cell RNA sequencing data from Gene Expression Omnibus (GEO) were analyzed using Scanpy. Immunohistochemistry was performed on formalin-fixed, paraffin-embedded (FFPE) ESCC tissues. PDCD10 was identified as a potential tumor-associated gene, and its association with clinicopathological factors and prognostic impact was evaluated using Kaplan-Meier survival and Cox regression analyses. Pathway analysis was performed to investigate the biological processes, and drug sensitivity profiling was conducted to identify compounds whose efficacy correlated with PDCD10 expression in ESCC cell lines. RESULTS: PDCD10, a signaling protein involved in cell proliferation and vascular development, showed significant amplification and over-expression in ESCC cases. High PDCD10 expression was associated with poor prognosis. Single-cell RNA sequencing confirmed its tumor-specific expression. GSEA revealed enrichment of mTORC1 signaling, E2F, and Myc target pathways in high PDCD10-expressing tumors. Drug sensitivity analysis identified Azelaic acid and Rebamipide as compounds whose efficacy correlated with PDCD10 expression in ESCC cell lines. CONCLUSION: PDCD10 could be a novel tumor-associated gene associated with tumor progression and poor prognosis in ESCC. Azelaic acid and Rebamipide are candidate therapeutic agents targeting PDCD10.
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Single-cell analysis highlights the role of CD4+ IFN-I-related T cells in Behcet's uveitis during Interferonα-2a therapy.
BACKGROUND: Behcet's disease (BD) involves multiple immune cells, but the mechanism by which interferon α-2a (IFNα-2a) exerts therapeutic effects on BD through immune cell modulation remains unclear. This study aimed to investigate the role of CD4 + IFN-I-related T cells in BD with active uveitis during IFNα-2a therapy. METHODS: A single-cell atlas of peripheral blood mononuclear cells (PBMCs) was constructed from BD patients with active uveitis, post-4-month IFNα-2a therapy BD patients, active BD patients, and healthy controls (HCs) by integrating in-house and public scRNA-seq data. Bulk mRNA sequencing of CD4 + T cells from active BD patients and HCs was performed for validation. Cell-cell interaction, in vitro coculture, and inhibitor experiments were used to explore the underlying mechanisms. RESULTS: CD4 + IFN-I-related T cells (characterized by high interferon-related gene expression) were significantly decreased in active BD patients but restored after IFNα-2a therapy. The LLT1-CD161 interaction intensity between CD4 + IFN-I-related T cells and NK cells was reduced in active BD and recovered post-therapy. CD4 + IFN-I-related T cells inhibited NK cell activation and IFN-γ secretion via the CD161 receptor. CONCLUSIONS: IFNα-2a therapy reverses the decreased frequency of CD4 + IFN-I-related T cells in active BD, which in turn inhibits the inflammatory phenotype of NK cells through LLT1-CD161 interaction, providing new insights into the therapeutic mechanism of IFNα-2a in BD.
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Response to Antiangiogenic Therapy Is Associated with AIMP Protein Family Expression in Glioblastoma and Lower-Grade Gliomas.
UNLABELLED: Glioblastoma (GBM) is a highly vascularized, heterogeneous tumor, yet antiangiogenic therapies have yielded limited survival benefits. The lack of validated predictive biomarkers for treatment response stratification remains a major challenge. Aminoacyl tRNA synthetase complex-interacting multicomplex proteins (AIMP) 1/2/3 have been implicated in central nervous system diseases, but their roles in gliomas remain unexplored. We investigated their association with angiogenesis and their significance as predictive biomarkers for antiangiogenic treatment response. In this multi-cohort retrospective study, we analyzed glioma samples from The Cancer Genome Atlas, Chinese Glioma Genome Atlas, REMBRANDT, Gravendeel, BELOB, and REGOMA trials, and four single-cell transcriptomic datasets. Multiomic analyses incorporated transcriptomic, epigenetic, and proteomic data. Kaplan-Meier and Cox proportional hazards models were used to assess the potential prognostic value of AIMPs in heterogeneous and homogeneous treatment groups. Using single-cell transcriptomics, we explored spatial and cell type-specific AIMP2 expression in GBM. AIMP1/2/3 expressions correlated significantly with angiogenesis across The Cancer Genome Atlas cancers. In gliomas, AIMPs were upregulated in tumor versus normal tissues, higher- versus lower-grade gliomas, and recurrent versus primary tumors (P < 0.05). Upon retrospective analysis of two clinical trials assessing different antiangiogenic drugs, we found that high-AIMP2 subgroups had improved response to therapies in GBM [REGOMA: HR, 4.75 (1.96-11.5), P < 0.001; BELOB: HR, 2.3 (1.17-4.49), P = 0.015]. AIMP2-cg04317940methylation emerged as a clinically applicable stratification marker. Single-cell analysis revealed homogeneous AIMP2 expression in tumor tissues, particularly in astrocyte-like cells, suggesting a mechanistic link to tumor angiogenesis. These findings provide novel insights into the role of AIMPs in angiogenesis, offering improved patient stratification and therapeutic outcomes in recurrent GBM. SIGNIFICANCE: This study identifies AIMP2 as a novel biomarker predictive of antiangiogenic treatment response in recurrent GBM. Through multiomic and single-cell analyses, AIMP2 is shown to be upregulated in aggressive gliomas and linked to angiogenesis. Its expression and methylation status offer a clinically applicable stratification tool, enabling more personalized therapeutic approaches and improved outcomes in patients receiving antiangiogenic therapies.
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Multi-omic analysis and validation reveal ZBP1 as a potential prognostic and immunotherapy-related biomarker in head and neck squamous cell carcinoma.
BACKGROUND: Patients with head and neck squamous cell carcinoma (HNSCC) exhibit unfavorable clinical outcomes, accompanied by high morbidity/mortality. In recent years, the management of HNSCC has encountered a significant obstacle. Z-DNA binding protein 1 (ZBP1) exerts crucial biological functions in chronic inflammatory disease and cancer. The aim of this research was to identify the possible function of ZBP1 in HNSCC. METHODS: The Cancer Genome Atlas (TCGA) database was used to collect the gene expression profile and corresponding clinical data. The gene expression, clinical prognosis, genetic alteration, immune characteristics, and subgroup analyses were performed. Meanwhile, an independent cohort (consisting of 66 tumor samples and 37 controls) was employed to validate the expression of ZBP1. RESULTS: Comparing to the normal controls, ZBP1 was upregulated in tumor samples. Low ZBP1 expression predicted undesirable clinical outcomes of HNSCC patients based on the survival analysis. Furthermore, the somatic mutations increased in low ZBP1 expression group. Immune characteristics analysis indicated a positive correlation of ZBP1 expression with the infiltration of immune cells, the expression of immunoregulatory genes and immune checkpoints. In the meantime, single-cell transcriptome analysis unveiled the expression of ZBP1 in tumor microenvironment (TME). In addition, differential gene expression analysis revealed that the expression of ZBP1 primarily contributes to the activation of T cells. Ultimately, ZBP1-associated prognostic and immune features in different subgroups of HNSCC patients were further investigated according to the subgroup analysis. CONCLUSION: Our study comprehensively disclosed that ZBP1 may have the potential to become a meaningful prognostic and immunotherapy-related biomarker for HNSCC.
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Programming human cell type-specific gene expression via an atlas of AI-designed enhancers.
Differentially active enhancers are key drivers of cell type specific gene expression. Active enhancers are found in open chromatin, which can be mapped at genome scale across tissue and cell types. Though incompletely understood, the relationship between chromatin accessibility and enhancer activity has been exploited to identify, model, and even design functional enhancers for selected cell types, but to what extent this design strategy can generalize across human cell and tissue types remains unclear. Here, we trained deep neural networks on a large corpus of chromatin accessibility data from hundreds of human biosamples. We used these models to generate an atlas of tens of thousands of synthetic enhancers, targeting hundreds of cell lines, tissues, and differentiation states, aiming to maximize accessibility in target samples and minimize it in all off-target ones. Experimental testing of thousands of designs in a representative subset of ten human cell types and in mouse retina demonstrated their function as specific enhancers, not only in the case of one-versus-all objectives but also when targeting two or three cell types. An explainable AI analysis, enabled by our large-scale enhancer measurements, allowed us to identify similarities and differences between the sequence grammar underlying accessibility and enhancer activity. Our results show that model-guided design of enhancers can help us decipher the cis-regulatory code governing cell type specificity and generate novel tools for selective targeting of human cell states.
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Dual Roles of Signal Transducer and Activator of Transcription 1 (STAT1) in Cancer: Expression Patterns, Prognostic Significance, and Immune Associations Across Multiple Tumor Types.
BACKGROUND: Signal transducer and activator of transcription 1 (STAT1) is a pivotal transcription factor that plays a dual role in cancer biology. It behaves as a tumor suppressor and, under certain conditions, as a promoter. Few studies have analyzed STAT1 in pan-cancers and explored its role in cancer biology. This study aimed to investigate the expression of STAT1 across various cancers at different stages. Additionally, we examined the promoter methylation of STAT1 and its impact on STAT1 expression, evaluated the functional states of STAT1 in different cancer types, analyzed the correlation between STAT1 expression and survival prognosis, and studied the tumor immune infiltration. Furthermore, we analyzed STAT1 expression across diverse immune subsets in cancer. Subsequently, we conducted an analysis of STAT1-protein interactions and studied the cancer hallmarks of STAT1 and its related proteins. METHODS: Various bioinformatics tools (Gene Expression Profiling Interactive Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), Kaplan-Meier Plotter, StarBase, Enrichr, and Tumor and Immune System Interaction Database (TISIDB)) and databases (Cancer Single-cell State Atlas (CancerSEA) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING)) were used in this study. We comprehensively investigated STAT1 protein expression across various types of cancer and the correlation between its expression and different tumor stages, DNA methylation, survival outcomes, and immune cell infiltration. Additionally, we examined the correlation between STAT1 expression and various immune subtypes of cancer, as well as the functional states of STAT1 in different cancer types. Moreover, we investigated the STAT1 protein interactions and cancer hallmarks of STAT1 and its related proteins. RESULTS: High STAT1 expression was found in 21 cancers and was differentially expressed across different clinical tumor stages and promoter methylation levels. In addition, we found that high expression correlated with better overall survival in some tumors, whereas it correlated with worse overall survival in other tumor types. Furthermore, the expression of STAT1 was associated with the level of immune infiltration in multiple tumors and different immune subtypes. We found that STAT1 expression had dual correlations (positive and negative) with different functional states in tumors, including angiogenesis and apoptosis. STAT1 protein interaction and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that 10 STAT1-interacting proteins were significantly enriched in cancer-related pathways. CONCLUSION: Our findings suggest that STAT1 may serve as a potential diagnostic and prognostic marker for several cancer types.