Single-Cell Transcriptome Analysis of Radiation Pneumonitis Mice.
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ABSTRACT:
SUBMITTER: Yang M
PROVIDER: S-EPMC9331247 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Radiation pneumonitis (RP) is one of the most important dose-limiting toxicities in the radiotherapy of thoracic tumors, which reduces the rate of local tumor control and overall survival and severely affects the patients' quality of life. Single-nucleotide polymorphisms (SNPs) have recently attracted increasing attention as biomarkers for predicting the development of RP. SNPs in inflammation-related, DNA repair-related, stress response-related and angiogenesis-related genes were proved to be associated with RP, with different underlying mechanisms. Radiogenomics focuses on the differences in radiosensitivity caused by gene sequence variation, which may prove helpful in investigating the abovementioned associations. In this review, we aimed to investigate the associations between RP and SNPs reported in recent studies and highlight the main content and prospects of radiogenomics.
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Project description:Fibrotic hypersensitivity pneumonitis (FHP) remains one of fatal interstitial pulmonary disease. Comprehensively dissecting the cellular heterogeneity of FHP paves the way for developing general gene therapeutic solutions for FHP. Here, utilizing an integrated strategy based on scRNA-seq, scTCR-seq, and bulk RNA-seq analysis of FHP profiles, we identified ten major cell types and 19 unique subtypes. FHP exhibited higher features of EMT and inflammation-promoting than normal control. In distinct subsets of lung macrophages in FHP, FN1high, PLA2G7high, and MS4A6Ahigh macrophages with predominant M2 phenotype exhibited higher activity of inflammatory responses and para-inflammation than other macrophages. KRT17high basal-like epithelial cells were significantly increased in FHP, and showed higher ability to induce EMT. We identified roles for ACTA2high, COL1A1high, and PLA2G2Ahigh fibroblasts in FHP, which were significantly related to interstitial fibrosis. NK cells and KLRG1+ effector CD8+ T cells had greater activity in inflammation-promoting. Our results provide a comprehensive portrait of cellular heterogeneity in FHP, and highlight the indispensable role of cell subpopulations in shaping the complexity and heterogeneity of FHP. These subpopulations are potentially key players for FHP pathogenesis.
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Project description:BackgroundIn non-small-cell lung cancer radiotherapy, radiation pneumonitis≥grade 2 (RP2) depends on patients' dosimetric, clinical, biological and genomic characteristics.MethodsWe developed a Bayesian network (BN) approach to explore its potential for interpreting biophysical signaling pathways influencing RP2 from a heterogeneous dataset including single nucleotide polymorphisms, micro RNAs, cytokines, clinical data, and radiation treatment plans before and during the course of radiotherapy. Model building utilized 79 patients (21 with RP2) with complete data, and model testing used 50 additional patients with incomplete data. A developed large-scale Markov blanket approach selected relevant predictors. Resampling by k-fold cross-validation determined the optimal BN structure. Area under the receiver-operating characteristics curve (AUC) measured performance.ResultsPre- and during-treatment BNs identified biophysical signaling pathways from the patients' relevant variables to RP2 risk. Internal cross-validation for the pre-BN yielded an AUC=0.82 which improved to 0.87 by incorporating during treatment changes. In the testing dataset, the pre- and during AUCs were 0.78 and 0.82, respectively.ConclusionsOur developed BN approach successfully handled a high number of heterogeneous variables in a small dataset, demonstrating potential for unraveling relevant biophysical features that could enhance prediction of RP2, although the current observations would require further independent validation.
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Project description:PurposeTo determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-β, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC).Methods and materialsSixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGFβ, TNFα, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade≥3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data.ResultsFive SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGFβ, VEGF, TNFα, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGFβ, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often.ConclusionsThis study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.
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Project description:Radiation therapy is a major treatment modality for management of non-small cell lung cancer. Radiation pneumonitis is a dose limiting toxicity of radiotherapy, affecting its therapeutic ratio. This review presents patient and treatment related factors associated with the development of radiation pneumonitis. Research focusing on reducing the incidence of radiation pneumonitis by using information about lung ventilation, imaging-based biomarkers as well as normal tissue complication models is discussed. Recent advances in our understanding of molecular mechanisms underlying lung injury has led to the development of several targeted interventions, which are also explored in this review.
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Project description:IntroductionRadiation pneumonitis is a critical complication that constrains the use of radiation therapy for thoracic malignancies, leading to substantial morbidity via respiratory distress and lung function impairment. The role of Natural killer (NK) cells in inflammatory diseases is well-documented; however, their involvement in radiation pneumonitis is not fully understood.MethodsTo explore the involvement of NK cells in radiation pneumonitis, we analyzed tissue samples for NK cell presence and function. The study utilized immunofluorescence staining, western blotting, and immunoprecipitation to investigate CXCL10 and ROS levels, autophagy activity, and NKG2D receptor dynamics in NK cells derived from patients and animal models subjected to radiation.ResultIn this study, we observed an augmented infiltration of NK cells in tissues affected by radiation pneumonitis, although their function was markedly diminished. In animal models, enhancing NK cell activity appeared to decelerate the disease progression. Concomitant with the disease course, there was a notable upsurge in CXCL10 and ROS levels. CXCL10 was found to facilitate NK cell migration through CXCR3 receptor activation. Furthermore, evidence of excessive autophagy in patient NK cells was linked to ROS accumulation, as indicated by immunofluorescence and Western blot analyses. The association between the NKG2D receptor and its adaptor proteins (AP2 subunits AP2A1 and AP2M1), LC3, and lysosomes was intensified after radiation exposure, as demonstrated by immunoprecipitation. This interaction led to NKG2D receptor endocytosis and subsequent lysosomal degradation.ConclusionOur findings delineate a mechanism by which radiation-induced lung injury may suppress NK cell function through an autophagy-dependent pathway. The dysregulation observed suggests potential therapeutic targets; hence, modulating autophagy and enhancing NK cell activity could represent novel strategies for mitigating radiation pneumonitis.
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Project description:Study questionHow can we study the full transcriptome of endometrial stromal and epithelial cells at the single-cell level?Summary answerBy compiling and developing novel analytical tools for biopsy, tissue cryopreservation and disaggregation, single-cell sorting, library preparation, RNA sequencing (RNA-seq) and statistical data analysis.What is known alreadyAlthough single-cell transcriptome analyses from various biopsied tissues have been published recently, corresponding protocols for human endometrium have not been described.Study design, size, durationThe frozen-thawed endometrial biopsies were fluorescence-activated cell sorted (FACS) to distinguish CD13-positive stromal and CD9-positive epithelial cells and single-cell transcriptome analysis performed from biopsied tissues without culturing the cells. We studied gene transcription, applying a modern and efficient RNA-seq protocol. In parallel, endometrial stromal cells were cultured and global expression profiles were compared with uncultured cells.Participants/materials, setting, methodsFor method validation, we used two endometrial biopsies, one from mid-secretory phase (Day 21, LH+8) and another from late-secretory phase (Day 25). The samples underwent single-cell FACS sorting, single-cell RNA-seq library preparation and Illumina sequencing.Main results and the role of chanceHere we present a complete pipeline for single-cell gene-expression studies, from clinical sampling to statistical data analysis. Tissue manipulation, starting from disaggregation and cell-type-specific labelling and ending with single-cell automated sorting, is managed within 90 min at low temperature to minimize changes in the gene expression profile. The single living stromal and epithelial cells were sorted using CD13- and CD9-specific antibodies, respectively. Of the 8622 detected genes, 2661 were more active in cultured stromal cells than in biopsy cells. In the comparison of biopsy versus cultured cells, 5603 commonly expressed genes were detected, with 241 significantly differentially expressed genes. Of these, 231 genes were up- and 10 down-regulated in cultured cells, respectively. In addition, we performed a gene ontology analysis of the differentially expressed genes and found that these genes are mainly related to cell cycle, translational processes and metabolism.Limitations, reasons for cautionAlthough CD9-positive single epithelial cells sorting was successfully established in our laboratory, the amount of transcriptome data per individual epithelial cell was low, complicating further analysis. This step most likely failed due to the high dose of RNases that are released by the cells' natural processes, or due to rapid turnaround time or the apoptotic conditions in freezing- or single-cell solutions. Since only the cells from the late-secretory phase were subject to more focused analysis, further studies including larger sample size from the different time-points of the natural menstrual cycle are needed. The methodology also needs further optimization to examine different cell types at high quality.Wider implications of the findingsThe symbiosis between clinical biopsy and the sophisticated laboratory and bioinformatic protocols described here brings together clinical diagnostic needs and modern laboratory and bioinformatic solutions, enabling us to implement a precise analytical toolbox for studying the endometrial tissue even at the single-cell level.
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Project description:Radiation pneumonitis (RP) is a common and fatal complication in thoracic radiation therapy. The immune microenvironment plays an important role in the RP development. However, the full scope of radiation immune changes over time remains unclear. In this study, a murine model of RP was established, and distinct early (10 days) and late phases (100 days) were defined. We conducted single-cell RNA sequencing and related RNA-seq and proteomics to explore the underlying mechanisms of persistent inflammation during RP. By examining the immunological effects of RP over time at the single-cell level, we shed light on its dynamic immunological effects of RP over time at single-cell resolution and provided potential therapeutic targets for clinical interventions.
2024-05-24 | GSE236049 | GEO