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Integrative single-cell and spatial transcriptomic analysis reveals that ATG13 enriched in cancer-associated fibroblasts is associated with the suppression of ferroptosis in colorectal cancer.
BACKGROUND: Colorectal cancer (CRC) progression and metastasis are primarily driven by dynamic changes within the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) exhibit significant heterogeneity within the TME and play a crucial role in regulating ferroptosis. Therefore, identifying novel ferroptosis-related biomarkers associated with CAFs could contribute to the development of personalized therapeutic strategies for cancer. METHODS: This study integrates single-cell sequencing data from 64 CRC samples and uses hierarchical clustering to identify cancer-associated fibroblast (CAF) subpopulations. We then combined spatial transcriptomics, hdWGCNA, CellChat, and Monocle analyses to characterize CAF subgroups. Single-cell and spatial transcriptomic data were integrated with Seurat to build a comprehensive spatial atlas. Multiplex immunohistochemical staining was used to analyze the spatial relationships of key genes with CAFs. Functional validation of these genes was performed with molecular docking, qPCR, Western blot, and both cellular and animal experiments. RESULTS: Single-cell data analysis identified five distinct CAF subpopulations, among which inflammatory cancer-associated fibroblasts (iCAFs) were significantly associated with the ferroptosis pathway and closely correlated with the proliferation and metastasis of malignant epithelial cells (p = 0.87). WGCNA revealed that the iCAFs-M10 module exhibited the strongest correlation with the expression of ferroptosis-related genes (cor = 0.6796). Further investigation identified ATG13 as a key hub gene, highly expressed in tumor tissues and significantly associated with poor patient prognosis. Spatial transcriptomics and multiplex immunohistochemistry (mIHC) results demonstrated that ATG13 was highly expressed in CAFs and co-localized with CAFs markers, such as α-SMA and Vimentin. In vitro and in vivo functional assays confirmed that ATG13 knockdown effectively inhibited the proliferation, migration, and invasion of colorectal cancer cells. Additionally, ferroptosis was induced upon ATG13 silencing, as evidenced by increased levels of GPX4, SLC7A11, ACSL4, MDA, Fe2⁺, GSH, and lipid peroxidation. In conclusion, this study reveals that ATG13, highly expressed in iCAFs, is associated with ferroptosis suppression in CRC, suggesting a potential CAF-tumor cell crosstalk axis that warrants further mechanistic investigation, thereby promoting the malignant progression of colorectal cancer. These findings provide potential targets for therapeutic strategies aimed at targeting the CAFs-ferroptosis axis. CONCLUSION: This study identifies the iCAFs subpopulation as playing a key role in regulating ferroptosis in CRC, with ATG13 acting as a negative regulator of ferroptosis that promotes tumor progression. These findings provide new insights and potential targets for understanding the mechanisms of ferroptosis in CRC and for the development of targeted therapies.
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A Single-cell Atlas of Developing Mouse Palates Reveals Cellular and Molecular Transitions in Periderm Cell Fate.
Cleft palate is one of the most common congenital craniofacial disorders that affects children's appearance and oral functions. Investigating the transcriptomes during palatogenesis is crucial for understanding the etiology of this disorder and facilitating prenatal molecular diagnosis. However, there is limited knowledge about the single-cell differentiation dynamics during mid-palatogenesis and late-palatogenesis, specifically regarding the subpopulations and developmental trajectories of periderm, a rare but critical cell population. Here, we explored the single-cell landscape of mouse developing palates from embryonic day (E) 10.5 to E16.5. We systematically depicted the single-cell transcriptomes of mesenchymal and epithelial cells during palatogenesis, including subpopulations and differentiation dynamics. Additionally, we identified four subclusters of palatal periderm and constructed two distinct trajectories of cell fates for periderm cells. Our findings reveal that claudin-family coding genes and Arhgap29 play a role in the non-stick function of the periderm before the palatal shelves contact, and Pitx2 mediates the adhesion of periderm during the contact of opposing palatal shelves. Furthermore, we demonstrate that epithelial-mesenchymal transition (EMT), apoptosis, and migration collectively contribute to the degeneration of periderm cells in the medial epithelial seam. Taken together, our study suggests a novel model of periderm development during palatogenesis and delineates the cellular and molecular transitions in periderm cell determination.
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The significance of immunogenic cell death related prognostic gene markers in colorectal cancer prognosis and antitumor immunity.
Immunogenic cell death (ICD) plays a critical role in the host’s antitumor immune response, and its dysregulation is linked to poor prognosis in colorectal cancer (CRC). Identifying ICD-related genes and developing prognostic models can enhance the prediction of patient outcomes and facilitate personalized treatments. Utilizing data from CRC patients in the Cancer Genome Atlas, we employed weighted gene co-expression network analysis, LASSO regression analysis, and multivariate Cox regression screening to identify immunogenic cell death-related prognostic genes (IPGs) in CRC patients. An IPGs scoring system was constructed, allowing for the stratification of patients into high-risk and low-risk groups based on the best cutoff ICD-RiskScore, with the Gene Expression Omnibus dataset serving as a validation cohort. We then examined the correlations between the high-risk and low-risk groups concerning clinicopathological features, immune infiltration, immunotherapy responses, and tumor mutational burden. Additionally, we analyzed the cellular landscape and cell-cell interactions in colorectal cancer at a single-cell resolution. A prognostic model comprising 12 immune-related prognostic genes (IPGs)—CAV2, NOXA1, TGFB2, WRNIP1, CCL22, ICAM2, APOBEC3F, COTL1, CTSD, IDO1, NFATC1, and RUNX3—was established, demonstrating a high area under the curve value in survival analysis, which indicates robust predictive performance. In comparison to the low-risk group, the high-risk group exhibited lower survival rates, higher mutation rates of genes, and was associated with more advanced tumor stages. Single-sample gene set enrichment analysis revealed that the low-risk group possessed a stronger immune surveillance function. Additionally, single-cell analysis uncovered a lower abundance of immune cells and an increased proportion of epithelial cells within tumor samples. The frequency of interactions among epithelial cells, endothelial cells, and fibroblasts was found to be elevated in tumor samples. Subsequently, validation of the prognostic genes revealed that COTL1 expression was significantly elevated in CRC tissues compared to adjacent normal tissues (P < 0.05). This study presents a prognostic model for colorectal cancer that integrates 12 immune-related genes. The model holds potential clinical value in predicting patient prognosis and guiding personalized treatment strategies. These findings also provide insights into the molecular mechanisms of immune cell dynamics in colorectal cancer and highlight potential therapeutic targets.
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Comprehensive analysis the prognostic and immune characteristics of mitochondrial transport-related gene SFXN1 in lung adenocarcinoma.
BACKGROUND: Mitochondria, which serve as the fundamental organelle for cellular energy and metabolism, are closely linked to the growth and survival of cancer cells. This study aims to identify and assess Sideroflexin1 (SFXN1), an unprecedented mitochondrial gene, as a potential prognostic biomarker for lung adenocarcinoma (LUAD). METHODS: The mRNA and protein levels of SFXN1 were investigated based on the Cancer Genome Atlas (TCGA) LUAD dataset, and then validated by real-time quantitative PCR, Western Blotting and immunohistochemistry from our clinical samples. The clinical correlation and prognostic value were evaluated by the TCGA cohort and verified via our clinical dataset (n = 90). The somatic mutation, drug sensitivity data, immune cell infiltration and single-cell RNA sequencing data of SFXN1 were analyzed through public databases. RESULTS: SFXN1 was markedly upregulated at both mRNA and protein levels in LUAD, and high expression of SFXN1 were correlated with larger tumor size, positive lymph node metastasis, and advanced clinical stage. Furthermore, SFXN1 upregulation was significantly associated with poor clinical prognosis. SFXN1 co-expressed genes were also analyzed, which were mainly involved in the cell cycle, central carbon metabolism, DNA repair, and the HIF-1α signaling pathway. Additionally, SFXN1 expression correlated with the expression of multiple immunomodulators, which act to regulate the tumor immune microenvironment. Results also demonstrated an association between SFXN1 expression and increased immune cell infiltration, such as activated CD8 + T cells, natural killer cells (NKs), activated dendritic cells (DCs), and macrophages. LUAD patients with high SFXN1 expression exhibited heightened sensitivity to multiple chemotherapies and targeted drugs and predicted a poor response to immunotherapy. SFXN1 represented an independent prognostic marker for LUAD patients with an improved prognostic value for overall survival when combined with clinical stage information. CONCLUSIONS: SFXN1 is frequently upregulated in LUAD and has a significant impact on the tumor immune environment. Our study uncovers the potential of SFXN1 as a prognostic biomarker and as a novel target for intervention in LUAD.
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Comprehensive single-cell atlas of colorectal neuroendocrine tumors with liver metastases: unraveling tumor microenvironment heterogeneity between primary lesions and metastases.
BACKGROUND: Colorectal neuroendocrine tumors with liver metastases (CRNELM) are associated with a poorer prognosis compared to their nonmetastatic counterparts. A comprehensive understanding of the tumor microenvironment (TME) heterogeneity between primary lesions (PL) and liver metastases (LM) could provide crucial insights for enhancing clinical management strategies for these patients. METHODS: We utilized single-cell RNA sequencing to analyze fresh tissue samples from CRNELM patients, aiming to elucidate the variations in TME between PL and LM. Complementary multidimensional validation was achieved through spatial transcriptomics, bulk RNA sequencing, and multiplex immunohistochemistry/immunofluorescence. RESULTS: Our single-cell RNA sequencing analysis revealed that LM harboured a higher proportion of CD8 + T cells, CD4 + T cells, NK cells, NKT cells, and B cells exhibiting a stress-like phenotype compared to PL. RGS5 + pericytes may play a role in the stress-like phenotype observed in immune cells within LM. MCs in PL (PL_MCs) and LM (LM_MCs) exhibit distinct activation of tumor-associated signaling pathways. Notably, COLEC11 + matrix cancer-associated fibroblasts (COLEC11_mCAFs) were found to be significantly associated with LM_MCs. Cell communication analysis unveiled potential targetable receptor-ligand interactions between COLEC11_mCAFs and LM_MCs. Multidimensional validation confirmed the prominence of the characteristic stress-like phenotypes, including HSPA6_CD8_Tstr, HSPA6_NK, and COLEC11_mCAFs in LM. Moreover, a higher abundance of COLEC11_mCAFs correlated with poorer survival rates in the neuroendocrine tumor patient cohort. CONCLUSION: Overall, our study provides the first single-cell analysis of the cellular and molecular differences between PL and LM in CRNELM patients. We identified distinct cell subsets and receptor-ligand interactions that may drive TME discrepancies and support metastatic tumor growth. These insights highlight potential therapeutic targets and inform strategies for better managing CRNELM patients.
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Identification of a novel prognostic marker ADGRG6 in pancreatic adenocarcinoma: multi-omics analysis and experimental validation.
BACKGROUND: Pancreatic adenocarcinoma (PAAD) ranks among the most lethal malignancies worldwide. Current treatment options have limited efficacy, underscoring the need for new therapeutic targets. METHODS: This study employed a multi-omics analytical framework to delve into the expression profiles and prognostic implications of ADGRG6 within the pan-cancer dataset of The Cancer Genome Atlas (TCGA) database, highlighting the prognostic value and potential carcinogenic role of ADGRG6 in PAAD, which was further validated using data from multiple PAAD cohorts in the Gene Expression Omnibus (GEO) database. To assess the role of ADGRG6 in the tumor microenvironment of PAAD, we evaluated immune infiltration using CIBERSORT, ssGSEA, xCell and Tracking Tumor Immunophenotype (TIP), and utilized single-cell sequencing data to explore cell-cell interactions. Further cellular and animal experiments, such as colony formation assay, transwell assay, western blot, real-time PCR, and tumor xenograft experiments, were used to investigate the effect of ADGRG6 on the proliferation, metastatic potential and immune marker expression of PAAD and the underlying mechanisms. RESULTS: ADGRG6 emerged as a potential prognostic biomarker and a therapeutic target for PAAD, which was further corroborated by data extracted from multiple PAAD cohorts archived in the GEO database. Single-cell sequencing and immune infiltration analyses predicted the positive correlation of ADGRG6 with the infiltration of immune cells and with the interaction between malignant cells and fibroblasts/macrophages within the PAAD microenvironment. In vitro cell assays demonstrated that ADGRG6 promoted the proliferation, metastatic potential and immune marker expression of PAAD cells by increasing protein level of mutated p53 (mutp53), which activated a spectrum of gain-of-functions to promote cancer progression via the EGFR, AMPK and NF-κB signaling cascades. Furthermore, subcutaneous xenograft experiments in mice demonstrated that ADGRG6 knockdown substantially suppressed the growth of engrafted PAAD tumors. CONCLUSIONS: ADGRG6 may serve as a novel prognostic marker and a therapeutic targets for PAAD, playing a crucial role in the proliferation, metastasis, and immune marker regulation of PAAD through elevating protein level of mutated p53.
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PRAME Expression in Melanoma is Negatively Regulated by TET2-Mediated DNA Hydroxymethylation.
Preferentially expressed Antigen in Melanoma (PRAME) and Ten-Eleven Translocation (TET) dioxygenase-mediated 5-hydroxymethylcytosine (5hmC) are emerging melanoma biomarkers. We observed an inverse correlation between PRAME expression and 5hmC levels in benign nevi, melanoma in situ, primary invasive melanoma, and metastatic melanomas via immunohistochemistry and multiplex immunofluorescence: nevi exhibited high 5hmC and low PRAME, whereas melanomas showed the opposite pattern. Single-cell multiplex imaging of melanoma precursors revealed that diminished 5hmC coincides with PRAME upregulation in premalignant cells. Analysis of The Cancer Genome Atlas and Genotype-Tissue Expression databases confirmed a negative relationship between TET2 and PRAME messenger RNA expression in melanoma. Additionally, 5hmC levels were reduced at the PRAME 5' promoter in melanoma compared with nevi, suggesting a role for 5hmC in PRAME transcription. Restoring 5hmC levels via TET2 overexpression notably reduced PRAME expression in melanoma cell lines. These findings establish a function of TET2-mediated DNA hydroxymethylation in regulating PRAME expression and demonstrate epigenetic reprogramming as pivotal in melanoma tumorigenesis.
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Bulk and single-cell transcriptomics of stomach adenocarcinoma provide prognostic insights via the application of a novel gene signature associated with manganese metabolism.
BACKGROUND: Gastric cancer (GC), originating from gastric mucosa epithelial cells, is a global health issue, ranking as the fifth most common cancer and fourth in cancer-related deaths. Stomach adenocarcinoma (STAD) accounts for 95% of GC cases. Emerging evidence suggests a link between manganese (Mn) metabolism and GC, but the role of Mn metabolism-related genes (MMRGs) in STAD is unclear. This study aims to bridge this gap of Mn metabolism through the development of a robust prognostic signature derived from The Cancer Genome Atlas (TCGA) data. METHODS: We used RNA-sequencing data and clinical information from TCGA to identify STAD subtypes and developed a Mn metabolism scoring model to predict STAD prognosis. RESULTS: An extensive clustering analysis of 115 prognostic MMRGs related to GC facilitated the distinction of two unique subtypes classified as Cluster 1 (C1) and Cluster 2 (C2). The subsequent Kaplan-Meier survival analysis revealed that the C1 subtype had a better survival rate than the C2 subtype. Additionally, a statistically significant difference was observed between the two subtypes in terms of patient age and tumor grade. The box plot examination revealed a marked difference in the immune cell populations, including a diminished presence of B cells, CD4+ T cells, endothelial cells, and macrophages in the C1 samples compared with the C2 samples. A majority of immune checkpoints, particularly CTLA4, HAVCR2, IGSF8, ITPRIPL1, LAG3, PDCD1, PDCD1LG2, and TIGIT, exhibited significantly higher expression levels in the C2 group than in the C1 group. Our findings revealed that a total of 13 genes were upregulated, while 1,146 genes were downregulated in the C1 cohort. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted significant pathways, including the extracellular matrix (ECM)-receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, the Gene Ontology (GO) analysis revealed that the enriched biological processes included ECM organization, cell-substrate adhesion, and cell-matrix adhesion. STAD patients were further categorized into high- and low-MMRG groups based on MMRGs. This meticulous analysis identified seven prognostic markers: APOD, AKR1B1, CGB5, GAMT, VTN, SERPINE1, and GPX3. The expression levels of two specific genes, APOD and GPX3, were found to be significantly increased in both the fibroblast and myofibroblast subtypes in STAD based on the singe-cell RNA-sequencing data. Box plots demonstrated that AKR1B1 and GAMT were expressed across all nine identified cell subtypes, while VTN and SERPINE1 were lowly expressed across the same nine subtypes. CONCLUSIONS: This study developed a prognostic model for STAD using the expression levels of MMRGs. Our findings provide insights that could inform future targeted therapeutic approaches.
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Redox Regulator GLRX Is Associated With Tumor Immunity in Glioma.
Glutaredoxin is central to cellular redox chemistry and regulates redox homeostasis and malignant progression of many cancers. In glioma, the role of its coding gene (GLRX) remains unclear. We aimed to elucidate the role of glutaredoxin at the transcriptome level and its clinical prognostic value in glioma. In total, we evaluated 1,717 glioma samples with transcriptome data and corresponding clinical data as well as single-cell sequencing data from 6 glioma patients from publicly available databases. Gene set variation analysis and gene ontology analysis were performed to reveal the biological function of GLRX. The immune cell enrichment score was calculated by GSVA analysis. Single-cell sequencing data was visualized by t-distributed stochastic neighbor embedding analysis. The prognostic value of GLRX in glioma was verified by the Kaplan-Meier curve and multivariate COX analysis. GLRX was found to be highly enriched in gliomas of higher grades with wild-type IDH, without 1p/19q co-deletion, and with a methylated MGMT promoter. Moreover, GLRX could be a potential marker for the mesenchymal molecular subtype of gliomas. The expression of GLRX was closely related to the tumor immune process, immune checkpoints, and inflammatory factors with GLRX being specifically expressed in M0 macrophages. GLRX is also shown to be an independent prognostic factor in glioma. Altogether, our study outcomes show that GLRX is highly enriched in malignant gliomas and is closely related to the tumor immune microenvironment. Therefore, GLRX-targeted cell redox regulatory therapy may enhance the efficacy of glioma immunotherapy.
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Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.
Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n = 414) and EMBL-EBI (n = 53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach.