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Characterization of the microenvironment in different immune-metabolism subtypes of cervical cancer with prognostic significance.
Introduction: Immune cell infiltration and metabolic reprogramming may have great impact on the tumorigenesis and progression of malignancies. The interaction between these two factors in cervical cancer remains to be clarified. Here we constructed a gene set containing immune and metabolism related genes and we applied this gene set to molecular subtyping of cervical cancer. Methods: Bulk sequencing and single-cell sequencing data were downloaded from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database respectively. Immune and metabolism related genes were collected from Immport and Kyoto encyclopedia of genes and genomes (KEGG) database respectively. Unsupervised consensus clustering was performed to identify the molecular subtypes. Cibersort was applied to evaluate the immune cells infiltration status. Differential expression analysis and Gene set enrichment analysis (GSEA) were performed to characterize the molecular pattern of different subtypes. Multivariate Cox regression analysis was used for prognosis prediction model construction and receiver operating characteristic (ROC) curve was used for performance evaluation. The hub genes in the model were verified in single-cell sequencing dataset and clinical specimens. In vitro experiments were performed to validate the findings in our research. Results: Three subtypes were identified with prognostic implications. C1 subgroup was in an immunosuppressive state with activation of mitochondrial cytochrome P450 metabolism, C2 had poor immune cells infiltration and was characterized by tRNA anabolism, and the C3 subgroup was in an inflammatory state with activation of aromatic amino acid synthesis. The area under the ROC curve of the constructed model was 0.8, which showed better performance than clinical features. IMPDH1 was found to be significantly upregulated in tumor tissue and it was demonstrated that IMPDH1 could be a novel therapeutic target in vitro. Discussion: In summary, our findings suggested novel molecular subtypes of cervical cancer with distinct immunometabolic profiles and uncovered a novel therapeutic target.
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Developmental stage-specific localization of CK1α protein in the mouse ovary.
Casein kinase 1 alpha (CK1α), a conserved serine/threonine kinase, regulates diverse cellular processes including signal transduction, cell cycle progression, and DNA replication. To define its spatiotemporal dynamics during mammalian ovarian development, we systematically analyzed CK1α protein expression from embryonic day (E) 14.5 to postnatal day (P) 56 in the mouse ovary using Western blotting, immunofluorescence (IF) on tissue sections, and IF on isolated primary granulosa cells and oocytes. Reanalysis of published single-cell RNA sequencing data revealed progressive upregulation of Csnk1a1 transcripts from E9.5 through early postnatal stages. At the protein level, CK1α expression significantly increased from E14.5 to P56, with stabilization after P28. Immunofluorescence showed CK1α localized predominantly to oocytes within primordial follicles from E14.5 to P7. Starting at P7, CK1α expression expanded to include granulosa cells of developing primary and secondary follicles. Quantitative fluorescence analysis confirmed that CK1α signal in granulosa cells increased significantly from P7 onward, while the signal in the oocytes gradually decreased throughout development process. In vitro validation confirmed robust CK1α localization in both isolated granulosa cells and oocytes, co-localizing with FSHR and DDX4, respectively. This study provides the first comprehensive spatiotemporal atlas of CK1α expression in the wild-type developing mouse ovary, revealing stage-specific localization patterns that suggest distinct roles in oocyte maintenance and granulosa cell differentiation during folliculogenesis.
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YTHDC1 Promotes Stemness Maintenance and Malignant Progression in Head and Neck Squamous Cell Carcinoma.
BACKGROUND: YTH domain containing 1 (YTHDC1), an N6-methyladenosine (m6A) modification reading protein, plays a key role in regulating RNA translation and degradation. However, the role of YTHDC1 in head and neck squamous cell carcinoma (HNSCC) cancer stem cells remains largely unknown. This study is aimed at investigating the role of YTHDC1 in HNSCC and exploring its role in regulating cancer stem cells. METHODS: RNA sequencing was used to detect differentially expressed genes (DEGs) between SCC9 spheres and SCC9 cells and to uncover molecular pathways and target molecules associated with CSCs. We detected YTHDC1 expression in The Cancer Genome Atlas (TCGA) database data and clinical samples. Subsequently, YTHDC1 gene suppression assays were performed in HNSCC cell lines to investigate the effect of YTHDC1 on tumor cell stemness maintenance, proliferation, and migration capacity. To further confirm the role of YTHDC1 in regulating cancer stem cells in HNSCC, we analyzed online HNSCC single-cell transcriptomic data to investigate YTHDC1 expression patterns at the single-cell level and the correlation of these levels with the expression of stem cell markers. RESULTS: YTHDC1 expression levels were significantly upregulated in SCC9 spheres, and YTHDC1 was aberrantly expressed in HNSCC tumor tissues. The increased YTHDC1 expression was closely correlated with the clinical characteristics of HNSCC patients. YTHDC1 regulates the malignant phenotype of HNSCC in both in vivo and in vitro studies. Further single-cell transcriptomic data analysis revealed that YTHDC1 positively correlated with malignant epithelial cell stemness capacity at the single-cell level, and that YTHDC1 was involved in regulating stemness maintenance in HNSCC. CONCLUSIONS: These findings suggest that YTHDC1 may serve as a biomarker for stem maintenance and malignant progression in HNSCC, providing new insights into the treatment of cancer.
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A novel T-cell proliferation-associated gene predicts prognosis and reveals immune infiltration in patients with oral squamous cell carcinoma.
OBJECTIVE: Oral squamous cell carcinoma (OSCC) is a highly malignant tumour, and the prediction of its prognosis remains challenging. The prognostic value of T-lymphocyte proliferation regulators in OSCC remains to be explored. DESIGN: We integrated mRNA expression profiles and relevant clinical information of OSCC patients from The Cancer Genome Atlas database. The expression and function of T-lymphocyte proliferation regulators and their relationship with overall survival (OS) were analysed. The T-lymphocyte proliferation regulator signature was screened using univariate Cox regression and least absolute shrinkage and selection operator coefficients and used to construct models for prognosis and staging prediction as well as for immune infiltration analysis. Final validation was performed using single-cell sequencing database and immunohistochemical staining. RESULTS: Most T-lymphocyte proliferation regulators in the TCGA cohort exhibited different expression levels between OSCC and paracancerous tissues. A prognostic model constructed using the T-lymphocyte proliferation regulator signature (RAN, CDK1, and CDK2) was used to categorise patients into high- and low-risk groups. The OS was significantly lower in the high-risk group than the low-risk group (p < 0.01). The predictive ability of the T-lymphocyte proliferation regulator signature was validated by receiver operating characteristic curve analysis. Immune infiltration analysis revealed different immune statuses in both groups. CONCLUSIONS: We established a new T-lymphocyte proliferation regulator signature that can predict the prognosis of OSCC. The results of this study will contribute to studies of T-cell proliferation and the immune microenvironment in OSCC to improve prognosis and immunotherapeutic response.
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Cancer-wide in silico analyses using differentially expressed genes demonstrate the functions and clinical relevance of JAG, DLL, and NOTCH.
Notch ligands [jagged (JAG) and, delta-like (DLL) families] and receptors [NOTCH family] are key regulators of Notch signaling. NOTCH signaling contributes to vascular development, tissue homeostasis, angiogenesis, and cancer progression. To elucidate the universal functions of the JAG, DLL, and NOTCH families and their connections with various biological functions, we examined 15 types of cancer using The Cancer Genome Atlas clinical database. We selected the differentially expressed genes (DEGs), which were positively correlated to the JAG, DLL, and NOTCH families in each cancer. We selected positive and negative hallmark signatures across cancer types. These indicated biological features associated with angiogenesis, hypoxia, KRAS signaling, cell cycle, and MYC targets by gene ontology and gene set enrichment analyses using DEGs. Furthermore, we analyzed single-cell RNA sequencing data to examine the expression of JAG, DLL, and NOTCH families and enrichment of hallmark signatures. Positive signatures identified using DEGs, such as KRAS signaling and hypoxia, were enriched in clusters with high expression of JAG, DLL, and NOTCH families. We subsequently validated the correlation between the JAG, DLL, and NOTCH families and clinical stages, including treatment response, metastasis, and recurrence. In addition, we performed survival analysis to identify hallmark signatures that critically affect patient survival when combining the expression of JAG, DLL, and NOTCH families. By combining the DEG enrichment and hallmark signature enrichment in survival analysis, we suggested unexplored regulatory functions and synergistic effects causing synthetic lethality. Taken together, our observations demonstrate the functions of JAG, DLL, and NOTCH families in cancer malignancy and provide insights into their molecular regulatory mechanisms.
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Identification of exosome-related genes signature based on bioinformatics and machine learning for prognostic prediction in colorectal cancer.
BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor with increasing incidence and mortality rates worldwide. Exosomes are secretory vesicles generated by the endosomal system within cells. Previous studies have reported that exosome-related genes (ERGs) are associated with the progression of malignancies. This study investigates the role of ERGs in CRC, evaluates their impact on CRC prognosis, and explores inter-individual differences among CRC patients in different risk groups. METHODS: Weighted Gene Co-expression Network Analysis (WGCNA) algorithm was employed to identify ERGs associated with CRC. Subsequently, various bioinformatics approaches, including enrichment analysis, consensus clustering, and survival analysis, were utilized to investigate the role of ERGs in individual CRC patients. Furthermore, exosome-related signature genes were refined using the Random Forest (RF) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms based on colon cancer samples from The Cancer Genome Atlas (TCGA) database. An ERG-related gene signature was then constructed to calculate the ERG-associated risk score for each patient, which was validated using data from the Gene Expression Omnibus (GEO) database. Based on the risk scores, we assessed the responsiveness of different CRC individuals to immunotherapy and chemotherapy. Finally, single-cell analysis provided deeper insights into the relationship between ERGs and CRC, and a nomogram was established to enhance their clinical utility. RESULTS: This study identified two ERG-related subtypes that exhibited significant differences in prognosis, enriched pathways, clinicopathological features, and immune characteristics. Moreover, CRC individuals with high ERG-related risk scores were associated with poor responsiveness to immunotherapy and increased sensitivity to various chemotherapeutic agents. Single-cell analysis revealed that ERGs were highly expressed in monocytes. The model developed in this study demonstrated strong predictive accuracy for assessing ERG-related risk in CRC patients. CONCLUSIONS: This study identified two hub genes, CUL4A and UCHL1, highlighting the diagnostic and prognostic significance of ERGs in CRC and offering new insights into CRC treatment. Additionally, the ERG signature plays a crucial role in predicting individualized prognosis and facilitating the development of novel therapeutic strategies for CRC patients. Nevertheless, further studies are necessary to bring statistically derived risk models into clinically applicable assays.
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The characteristics and functional significance of disulfidptosis-related genes in head and neck squamous cell carcinoma.
Disulfidptosis is a newfound programmed cell death (PCD) mode characterized by disulfide stress. Nevertheless, the characteristics and functional significance of disulfidptosis-related genes in head and neck squamous cell carcinoma (HNSCC) are still largely unknown. In this study, several computer-aided bioinformatic analyses were performed. The Nonnegative Matrix Factorization (NMF) method classified The Cancer Genome Atlas (TCGA) patients into two clusters according to the expression of disulfidptosis-related genes. The relative compositions of cells in the tumor microenvironment (TME), mutant landscape, lasso regression analysis, and predicted clinical outcome were performed by analyzing bulk RNA-sequencing data. Besides, single-cell sequencing data (scRNA) was analyzed by Seurat, CopyKAT, and monocle2 to reveal the expression characteristics of disulfidptosis-related genes. Moreover, the spatial distribution characteristics of each cell subgroup in the section and the functional significance of cancer-associated fibroblasts (CAFs) were elucidated by STUtility, SpaCET, and SPATA2. Here, two clusters with different expression characteristics of disulfidptosis-related genes were identified. Cluster 1 (C1) patients had a worse prognosis and a higher proportion of stromal cells but lower effector T cell infiltration than cluster 2 (C2). A novel prognostic model was established and verified in our patient cohort. Additionally, diploid and inflammatory CAFs (iCAFs) showed higher disulfidptosis-related gene expression levels. Furthermore, the CCNC and CHMP1B expressions significantly changed following CAFs differentiation. Disulfidptosis-related genes exhibited extensive and differential spatial expression on tissue sections. Collectively, our study may contribute to revealing the function of disulfidptosis, and improve the expansion of knowledge of crosstalk between cancer cells and CAFs.
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Correlation between oncogene integrator complex subunit 7 and a poor prognosis in lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common types of cancer worldwide with high incidence and mortality rates. The integrator complex subunit 7 (INTS7) encodes a subunit of the integrator complex that mediates small-nuclear ribonucleic acid (RNA) processing and has been shown to be associated with RNA polymerase II. However, the clinical significance of INTS7 in LUAD is still not clear and needs to be investigated. METHODS: The single-cell sequencing of a publicly available data set was conducted to compare the expression levels and percentages of INTS7 in lung malignant cells at different classifications and stages. Further, 33 cancer types from The Cancer Genome Atlas (TCGA) database were analyzed, protein-protein interaction (PPI) networks were constructed, and functional annotations were undertaken for the INTS7 gene. INTS7 small-interfering RNAs were transfected into LUAD cell lines, and cell biological behaviors, such as migration, invasion, apoptosis and proliferation capacity, were then examined. RESULTS: We found that the expression of INTS7 was significantly more upregulated in the LUAD tissues than the adjacent normal tissues. Increased INTS7 messenger RNA expression was correlated with TNM (tumor node metastasis classification) stage and gender in LUAD patients. Further, the Kaplan-Meier survival analysis indicated that LUAD patients with high INTS7 expression levels had a worse prognosis than those with low INTS7 expression levels. Finally, we found that silencing INTS7 inhibited LUAD cell viability and invasion in vitro. CONCLUSIONS: These results suggest that INTS7 can be used as a potential therapy target and prognostic marker for LUAD. Further, INTS7 may aggravate migration and invasion, induce the proliferation, and attenuate the apoptosis capacity of cells in LUAD.
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Sex differences orchestrated by androgens at single-cell resolution.
Sex differences in mammalian complex traits are prevalent and are intimately associated with androgens1-7. However, a molecular and cellular profile of sex differences and their modulation by androgens is still lacking. Here we constructed a high-dimensional single-cell transcriptomic atlas comprising over 2.3 million cells from 17 tissues in Mus musculus and explored the effects of sex and androgens on the molecular programs and cellular populations. In particular, we found that sex-biased immune gene expression and immune cell populations, such as group 2 innate lymphoid cells, were modulated by androgens. Integration with the UK Biobank dataset revealed potential cellular targets and risk gene enrichment in antigen presentation for sex-biased diseases. This study lays the groundwork for understanding the sex differences orchestrated by androgens and provides important evidence for targeting the androgen pathway as a broad therapeutic strategy for sex-biased diseases.
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A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution.
The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed the unique marker genes of many neuronal subtypes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study's translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard ( http://harvard.heavy.ai:6273/ ) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data.