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High Expression of TACC3 Is Associated with the Poor Prognosis and Immune Infiltration in Lung Adenocarcinoma Patients.
BACKGROUND: Lung adenocarcinoma (LUAD) has been recognized as one of the commonest aggressive malignant tumors occurring in humans. The transforming acidic coiled-coil-containing protein 3 (TACC3) seems to be a probable prognostic marker and treatment target for non-small-cell lung cancer (NSCLC). Nevertheless, there exist no reports on the association between TACC3 and immunotherapy or other therapeutic interventions in LUAD. METHODS: Premised on the data accessed from The Cancer Genome Atlas- (TCGA-) LUAD, we carried out bioinformatics analysis. The TACC3 expression in LUAD was analyzed utilizing the GEPIA. A survival module was constructed to evaluate the effect of TACC3 on the survival of patients with LUAD. Logistic regression was undertaken to examine the relationship between TACC3 expression and clinical factors. Protein-protein interaction analysis was performed in the GeneMANIA database, and enrichment analysis and identification of predicted signaling pathways were performed using Gene Ontology and Kyoto Encyclopedia of Genes. Additionally, the Cox regression was used to assess the clinicopathologic features linked to the overall survival in TCGA patients. Lastly, we investigated the link between TACC3 and tumor-infiltrating immune cells (TIICs) through CIBERSORT and the "Correlation" module of GEPIA. The association between TACC3 gene expression and drug response was analyzed using the CellMiner database to predict drug sensitivity. RESULTS: The outcomes illustrated that TACC3 was upregulated and considerably correlated with dismal prognosis in LUAD patients. Moreover, the multivariate Cox regression analysis depicted TACC3 as an independent prognostic marker in LUAD patients. It was also revealed that the expression of TACC3 was related to clinical stage (P = 0.014), age (P = 0.002), and T classification (P ≤ 0.018). Moreover, we discovered that the expression of TACC3 was considerably linked to a wide range of TIICs, especially the T cells and NK cells. Single-cell results found that TACC3 was mainly expressed in the immune cells (especially tprolif cells) and malignant cells. TACC3 gene expression was positively correlated with TMB and MSI, and TACC3 may provide a prediction of the efficacy of immunotherapy. Moreover, the correlation analysis between TACC3 gene expression and immune checkpoint gene expression revealed that TACC3 may coordinate the activities of these ICP genes in different signal transduction pathways. TACC3 is related to biological progress (BP), cellular component (CC), and molecular function (MF). The pathways involved in the interaction network involving TACC3 include nonhomologous end-joining, RNA transport, pantothenate and CoA biosynthesis, homologous recombination, and nucleotide excision repair. Furthermore, we investigated the association between the expression of TACC3 and the use of antitumor drugs, and TACC3 was positively correlated with response to most drugs. CONCLUSION: The findings from this research offer robust proof that the expression of TACC3 could be a prognostic marker correlated with TIICs in LUAD. TACC3 can also provide new ideas for immunotherapy as a potential therapeutic target.
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Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer.
Bladder cancer (BLCA) is the tenth most commonly diagnosed cancer and poses a significant challenge due to its complexity and associated high morbidity and mortality rates in the absence of optimal treatment. The tumor microenvironment (TME) is recognized as a critical factor in tumor initiation, progression and therapeutic response, and offers numerous potential targets for intervention. A comprehensive understanding of immune infiltration patterns in BLCA is essential for the development of effective prevention and treatment strategies. In this study, bioinformatics analysis was used to identify differentially expressed genes (DEGs) and tumor-infiltrating immune cells (TIICs) between BLCA tissues and adjacent normal tissues. Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis were used to identify the top 10 hub genes with the most significant co-expression effects, and their potential relationship with patient prognosis was then predicted. The random survival forest (RSF) model was used to further identify six variables among the hub genes and establish a novel scoring system, defined as the tumor-infiltrating immune score (TIIS) to predict the prognosis of BLCA patients. In addition, the correlation analysis between TIIS and drug sensitivity was investigated using the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases. Patients with high TIIS were found to have a poor prognosis but may be more sensitive to Cisplatin and certain novel agents. This study provided a systematic analysis of immune cell infiltration in BLCA and established TIIS to predict patient prognosis and the efficacy of specific drugs in the treatment of BLCA.
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Spatial Transcriptomics Reveals Injured Cells, Signature Genes, and Communication Patterns in the Cyst Microenvironment of Polycystic Kidney Disease.
KEY POINTS: Myofibroblasts and injury repair-related cell types were exclusively observed in polycystic kidney disease and enriched within the cyst microenvironment. Cyst-associated gene signature of 45 genes with decreased expression further away from the cysts was largely related to inflammation. Communication in low-inflamed cystic microdomains related to cellular signaling, morphogenesis, and inflammation in polycystic kidney disease. BACKGROUND: Changes in the cyst microenvironment in polycystic kidney disease (PKD) may drive progressive cyst formation. Bulk-cell and single-cell RNA sequencing have advanced our understanding of altered signaling; however, the lack of spatial information has limited our insights into local gene expression and cellular communication near cysts. METHODS: We used wild-type and Pkd1 -deficient mouse kidneys to generate 10× Genomics Visium Spatial Gene Expression datasets. Using our single-cell mouse kidney atlas and single-cell sequencing data for spot deconvolution, we enhanced resolution and estimated enriched cell types. We analyzed spatial gene expression patterns and used a cyst-centered analysis to identify cyst-associated gene signature. Cell communication near cysts was investigated, identifying key ligand-receptors. Prioritized key factors were validated in tissues. RESULTS: We observed enrichment of fibroblasts, injury repair-related cell types, and diverse immune populations in PKD. Injury repair-related cells were exclusively observed in PKD, predominantly localized within immune cell-dense regions near cysts. These cells collectively contributed to the altered gene expression profile in PKD, including cyst-associated signature genes related to inflammatory processes. Analysis of cellular communication in less-inflamed regions around cysts revealed the involvement of multiple cell types. Key ligand-receptor interactions were associated with cytokine signaling, fibrosis, cellular development, and repair. These included Angpt2 , C3 , Csf1 , Cxcl12 , Il34 , Gas6 , Il16 , Mdk , Mif , Ptn , Sfrp2 , Spp1 , Sdc1 , Tnc , Tnfsf12 , and Wnt5a . In addition, extracellular matrix (ECM) proteins implicated in immune response, ECM remodeling, cell adhesion, and cell signaling were identified, such as Adam9 , Adam10 , Col1a1, Col3a1, Col4a2, Lamb2, Lamc1, Efnb1 , Efnb2 , Thbs1, Thbs2 , and Vcam1 . Immunohistochemistry confirmed expression of Syndecan-1-Collagen IV, Midkine-Integrin β 1, CSF-1, Pleiotrophin, and Tenascin-C in cystic kidneys. CONCLUSIONS: Spatial transcriptomics in PKD revealed enrichment of (myo)fibroblasts, immune, and injury repair-related cells near cysts, creating a (pro)inflammatory and (pro)fibrotic niche. Key ligand-receptor and ECM interactions were identified and validated.
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Spatial Proteomics for Further Exploration of Missing Proteins: A Case Study of the Ovary.
In the quest for "missing proteins" (MPs), the proteins encoded by the human genome still lacking evidence of existence at the protein level, novel approaches are needed to detect this challenging group of proteins. The current count stands at 1,343 MPs, and it is likely that many of these proteins are expressed at low levels, in rare cell or tissue types, or the cells in which they are expressed may only represent a small minority of the tissue. Here, we used an integrated omics approach to identify and explore MPs in human ovaries. By taking advantage of publicly available transcriptomics and antibody-based proteomics data in the Human Protein Atlas (HPA), we selected 18 candidates for further immunohistochemical analysis using an exclusive collection of ovarian tissues from women and patients of reproductive age. The results were compared with data from single-cell mRNA sequencing, and seven proteins (CTXN1, MRO, RERGL, TTLL3, TRIM61, TRIM73, and ZNF793) could be validated at the single-cell type level with both methods. We present for the first time the cell type-specific spatial localization of 18 MPs in human ovarian follicles, thereby showcasing the utility of the HPA database as an important resource for identification of MPs suitable for exploration in specialized tissue samples. The results constitute a starting point for further quantitative and qualitative analysis of the human ovaries, and the novel data for the seven proteins that were validated with both methods should be considered as evidence of existence of these proteins in human ovary.
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Intratumoral tertiary lymphoid structure (TLS) maturation is influenced by draining lymph nodes of lung cancer.
BACKGROUND: Tertiary lymphoid structure (TLS) is an organized infiltration of immune cells, showing features of germinal center (GC) commonly seen in secondary lymphoid organs. However, its relationship with tumor-draining lymph nodes (TDLNs) has not been studied and we hypothesized that TDLN may influence maturation of intratumoral TLS in non-small cell lung cancer (NSCLC). METHODS: Tissue slides of 616 patients that had undergone surgeries were examined. Cox proportional hazard regression model was used to assess risk factors of patients' survival, and logistic regression model was used for their relationship with TLS. Single-cell RNA-sequencing (scRNA-seq) was employed to explore transcriptomic features of TDLNs. Immunohistochemistry, multiplex immunofluorescence and flow cytometry were performed to analyze cellular composition. Cellular components of NSCLC samples from The Cancer Genome Atlas database were inferred with Microenvironment Cell Populations-counter (MCP-counter) method. Murine NSCLC models were used to dissect underlying mechanisms for relationship between TDLN and TLS maturation. RESULTS: While GC+ TLS was associated with better prognosis, GC- TLS was not. TDLN metastasis reduced the prognostic relevance of TLS, and was associated with less GC formation. Primary tumor sites showed reduced B cell infiltration in TDLN-positive patients, and scRNA-seq revealed diminished memory B cell formation in tumor-invaded TDLNs, together with an emphasis on weakened interferon (IFN)-γ response. Murine NSCLC models revealed that IFN-γ signaling is involved in memory B cell differentiation in TDLNs and GC formation in primary tumors. CONCLUSIONS: Our research emphasizes the influence of TDLN on intratumoral TLS maturation and suggests a role of memory B cells and IFN-γ signaling in this communication.
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Specific depletion of TIGIThigh CD226- clonally expanded intratumoral Tregs defines safe and effective TIGIT targeting.
BACKGROUND: Global clinical programs based on TIGIT (T cell immunoglobulin and ITIM domain) blockade have been terminated due to inadequate clinical efficacy. New approaches are needed to increase the antitumor activity of anti-TIGIT-based immunotherapy. METHODS: Multiomics analyses, including single-cell RNA sequencing (scRNA-seq), single-cell TCR sequencing (scTCR-seq), and The Cancer Genome Atlas bulk RNA-seq, were performed to profile TIGIT and the costimulator CD226 expression and assess intratumoral regulatory T cells (Tregs) clonality, with validation by flow cytometry in murine and patient-derived tumor-infiltrating lymphocytes. The therapeutic efficacy of anti-TIGIT antibodies (αTIGIT), including αTIGIT-IgG1-wild-type (WT), αTIGIT-IgG1-WT with enhanced antibody-dependent cellular cytotoxicity (ADCC) activity (αTIGIT-IgG1-ADCC), αTIGIT-IgG4-WT, and tiragolumab, was evaluated in MC38 tumors-inoculated humanized TIGIT knock-in mice (Tigith/h , Tigith/m ). Tumor microenvironment alterations were analyzed using flow cytometry and scRNA/TCR-seq. Antibody binding affinity and ADCC activity were assessed via biolayer interferometry and in vitro ADCC assays. Safety profiles were examined in a murine immune-related adverse events model through growth monitoring, survival analysis, and histopathological evaluation. RESULTS: Using mouse models and clinical sample analysis, we identified a population of TIGIThigh CD226- clonally expanded intratumoral Tregs as a major barrier limiting the ability of TIGIT blockade to enhance effector cell function. αTIGIT-IgG1-ADCC specifically targeted and eliminated the TIGIThigh CD226- clonally expanded Treg subset, resulting in a marked improvement in antitumor efficacy compared with WT and clinically unsuccessful αTIGIT. Mechanistically, removal of these Tregs through αTIGIT-IgG1-ADCC relieved their suppression of stem-like CD4+ T cells, facilitating their differentiation into T helper cell 1 (Th1) effector cells. Th1-derived interferon-gamma (IFN-γ) further enhanced the functionality of tumor-infiltrating CD8+ T cells. Importantly, the presence of clonally expanded intratumoral Tregs and the suppression of stem-like CD4+ T cells correlated with poor immunotherapy response in patients with non-small cell lung cancer. CONCLUSIONS: Targeted elimination of clonally expanded intratumoral Tregs is essential to unlock the full therapeutic potential of αTIGIT. These novel findings provide a key rationale and strategic direction for overcoming the limitations of current αTIGIT-based cancer immunotherapy.
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Identification of fatty acid oxidation-related subtypes by integrated analysis of bulk- and single-cell transcriptome profiling in colorectal cancer.
BACKGROUND: As one of the major metabolic reprogramming pathways, fatty acid oxidation (FAO) contributes to rapid progression in tumor cells. Nevertheless, the genomic patterns of patients' FAO levels in colorectal cancer (CRC) remain unknown. Hence, it is crucial to identify the interplay mechanisms of molecular biochemical features of FAO in CRC. METHODS: Data of patients with CRC were accessed from The Cancer Genome Atlas (TCGA). Unsupervised consensus clustering related to FAO sores was conducted. The differentially expressed genes (DEGs) were screened by clustering according to FAO status polarized in TCGA, followed by the construction of the scores of genes related to FAO (GFAO_Score). Enrichment of FAO and carcinogenesis at the cell level were calculated based on the single-cell RNA (scRNA) sequencing analysis. The clinical values and drug analysis of GFAO_Score were evaluated by external validation cohorts from Gene Expression Omnibus (GEO) datasets. RESULTS: We classified patients into two distinct FAO clusters which indicated those with lower FAO levels had poor prognosis and high enrichment of carcinogenic-gene pathways. Further, the high FAO-enriched subtypes in epithelial cells revealed carcinogenesis. Three FAO-related genes (ZFHX4, AQP8, and AKR1B10) were screened to construct the GFAO_Score. The high GFAO_Score group leaned toward advanced CRC and unfavorable survival outcomes in the validation cohort. The low GFAO_Score group possessed a better response to immunotherapy and exhibited lower IC50 (50% inhibition concentration) values for certain chemotherapy drugs, such as 5-fluorouracil, irinotecan, oxaliplatin, paclitaxel, and camptothecin. CONCLUSIONS: FAO patterns vary in patients with CRC. The GFAO_Score might contribute to the precise screening of patients according to metabolism reprogramming and optimization of strategies in clinical practice.
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Acute Inflammation Drives Corneal Pathological Regeneration.
PURPOSE: This study aimed to characterize transcriptional and epigenetic remodeling in the cornea induced by acute inflammation. METHODS: Limbal-corneal tissues were collected on days 5 and 10 after intrastromal administration of lipopolysaccharide or PBS. ScRNA-seq and scATAC-seq were used to delineate the transcriptomic and epigenomic atlas of the inflamed cornea, following the Seurat and Signac pipelines. Immunofluorescence was performed to assess changes in corneal epithelial markers and immune cell infiltration. RESULTS: We identified 16 cell clusters, including ten epithelial cell subpopulations, keratocytes, fibroblasts, corneal endothelial cells, blood vessel cells, lymphatic vessel cells, and immune cells. Lipopolysaccharide induced the infiltration of five major immune cell types: neutrophils, MHC-II⁻ macrophages, MHC-II⁺ macrophages, T cells, and natural killer cells. We characterized gene expression and chromatin accessibility dynamics across all cell types during the inflammatory response, revealing cell-type-specific gene regulatory elements and cis-regulatory chromatin interactions. Regulon activity and motif accessibility analyses identified critical transcription factors that drive distinct inflammatory response programs. Inflammation was found to inhibit limbal stem/progenitor cell differentiation. CellChat analysis revealed a set of secreted intercellular crosstalk signals among all cell types. CONCLUSIONS: Our work provides a comprehensive, time-resolved single-cell transcriptomic and epigenomic atlas of the inflamed cornea, defining cellular functional heterogeneity, cis-regulatory networks, and intercellular communication during corneal pathological regeneration. These findings offer valuable insights into corneal pathology.
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Retinol-driven Gene Signatures Predict Lung Adenocarcinoma Outcomes and Highlight PAICS as a Therapeutic Opportunity.
UNLABELLED: Retinol, a pivotal regulator of cellular growth and apoptosis, has garnered substantial attention for its intricate involvement in cancer development. To explore Vitamin A's impact on lung adenocarcinoma (LUAD), we utilized comprehensive datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to dissect the intricate role of retinol in cancer progression. The unsupervised clustering analysis, grounded on retinol metabolism gene sets, divided patients into two distinct clusters, with cluster 1 exhibiting significantly inferior survival outcomes. Through differential analysis, we uncovered 349 differentially mutated and 394 differentially expressed genes between these clusters. Leveraging these discoveries, we built a seven-gene signature model that precisely predicted poorer survival for patients with a higher risk score, which was subsequently validated in four independent GEO cohorts, demonstrating its robustness and reliability. Our drug sensitivity analysis further revealed that high-risk patients were more susceptible to gefitinib and erlotinib. Notably, leveraging gene dependency scores and RNA-seq data from LUAD cell lines, we identified Phosphoribosylaminoimidazole Carboxylase And Phosphoribosylaminoimidazolesuccinocarboxamide Synthase (PAICS) as a potential therapeutic target. Single-RNA sequencing confirmed PAICS's predominant expression in cancer cells, and functional assays underscored its oncogenic role in promoting cell proliferation, migration, and invasion. These novel findings offer profound insights into potential therapeutic avenues for LUAD patients with poor prognoses, paving the way for future research endeavors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43657-025-00223-y.
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TCGA-based identification of prognostic biomarkers and candidate traditional Chinese medicine compounds in papillary thyroid carcinoma: An observational study.
This study aimed to identify prognostic genes associated with papillary thyroid carcinoma (PTC) and explore candidate traditional Chinese medicine (TCM) compounds using integrated bioinformatics and molecular docking. In this observational study, PTC gene expression profiles and clinical data were obtained from The Cancer Genome Atlas. Differentially expressed genes were screened using differential-expression sequencing (DESeq2), followed by protein-protein interaction network analysis to identify hub genes. Their expression, diagnostic value, immune relevance, prognostic significance, protein-level validation, and single-cell distribution were assessed using gene expression profiling interactive analysis, receiver operating characteristic analysis, immune infiltration analysis, Kaplan-Meier survival analysis, the human protein atlas, and single-cell RNA-sequencing data. Candidate TCM compounds were predicted using symptom mapping (SymMap) and the TCM Systems Pharmacology Database and Analysis Platform, and molecular docking was performed to evaluate potential ligand-target interactions. Five hub genes, colony-stimulating factor 2, apolipoprotein E, fibronectin 1 (FN1), collagen type I alpha 1 chain (COL1A1), and intercellular adhesion molecule 1, were identified and found to be significantly upregulated in PTC tissues, with diagnostic value in receiver operating characteristic analysis. Immune infiltration analysis showed associations with macrophages, dendritic cells, and T helper 1 cells, whereas single-cell analysis demonstrated heterogeneous expression across immune and stromal cell populations, including fibroblasts. Higher FN1 and COL1A1 expression was associated with poorer outcomes. Immunohistochemistry supported the expression patterns, while single-cell analysis provided exploratory cell-type-level context for the cellular distribution of selected genes. Ginseng and Smilax glabra were predicted as common candidate TCMs, and docking suggested favorable binding between their active compounds and selected hub targets. Colony-stimulating factor 2, apolipoprotein E, FN1, COL1A1, and intercellular adhesion molecule 1 may be biologically relevant hub genes in PTC, while FN1 and COL1A1 may have prognostic value. Predicted TCM compounds provide preliminary computational evidence for possible compound-target interactions, requiring experimental and clinical validation.