An interactive murine single-cell atlas of the lung responses to radiation injury

High-dose vitamin C attenuates radiation-induced pulmonary fibrosis by targeting S100A8 and S100A9

Radiation-induced pulmonary fibrosis (RIPF) is a frequently encountered late complication in patients undergoing radiation therapy, presenting a substantial risk to patient mortality and quality of life. The pathogenesis of RIPF remains unclear, and current treatment options are limited in efficacy. High-dose vitamin C has demonstrated potential when used in conjunction with other adjuvant therapies due to potent anticancer properties. However, the potential relationship between high-dose vitamin C and RIPF has not yet been explored in existing literature. In our study, the RIPF model and the LLC tumor model were used as two animal models to explore how high-dose vitamin C can improve RIPF without hampering the antitumour efficacy of radiotherapy. The impact of high-dose vitamin C on RIPF was assessed through various assays, including micro-CT, HE staining, Masson staining, and immunohistochemistry. Our results indicated that administering high-dose vitamin C 2 days before radiation and continuing for a duration of 6 weeks significantly inhibited the progression of RIPF. In order to explore the mechanism by which high-dose vitamin C attenuates RIPF, we utilized RNA-seq analysis of mouse lung tissue in conjunction with publicly available databases. Our findings indicated that high-dose vitamin C inhibits the differentiation of fibroblasts into myofibroblasts by targeting S100A8 and S100A9 derived from neutrophils. Additionally, the combination of high-dose vitamin C and radiation demonstrated enhanced inhibition of tumor growth in a murine LLC tumor model. These results revealed that the combination of radiotherapy and high-dose vitamin C may offer a promising therapeutic approach for the clinical management of thoracic tumors and the prevention of RIPF.

TNKS1BP1 mediates AECII senescence and radiation induced lung injury through suppressing EEF2 degradation

BACKGROUND

Although recent studies provide mechanistic understanding to the pathogenesis of radiation induced lung injury (RILI), rare therapeutics show definitive promise for treating this disease. Type II alveolar epithelial cells (AECII) injury in various manner results in an inflammation response to initiate RILI.

RESULTS

Here, we reported that radiation (IR) up-regulated the TNKS1BP1, causing progressive accumulation of the cellular senescence by up-regulating EEF2 in AECII and lung tissue of RILI mice. Senescent AECII induced Senescence-Associated Secretory Phenotype (SASP), consequently activating fibroblasts and macrophages to promote RILI development. In response to IR, elevated TNKS1BP1 interacted with and decreased CNOT4 to suppress EEF2 degradation. Ectopic expression of EEF2 accelerated AECII senescence. Using a model system of TNKS1BP1 knockout (KO) mice, we demonstrated that TNKS1BP1 KO prevents IR-induced lung tissue senescence and RILI.

CONCLUSIONS

Notably, this study suggested that a regulatory mechanism of the TNKS1BP1/CNOT4/EEF2 axis in AECII senescence may be a potential strategy for RILI.

A systematic overview of single-cell transcriptomics databases, their use cases, and limitations

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of transcriptomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Such platforms can help bridge the gap between computational and wet lab scientists through user-friendly web-based interfaces needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

A point cloud segmentation framework for image-based spatial transcriptomics

Recent progress in image-based spatial RNA profiling enables to spatially resolve tens to hundreds of distinct RNA species with high spatial resolution. It presents new avenues for comprehending tissue organization. In this context, the ability to assign detected RNA transcripts to individual cells is crucial for downstream analyses, such as in-situ cell type calling. Yet, accurate cell segmentation can be challenging in tissue data, in particular in the absence of a high-quality membrane marker. To address this issue, we introduce ComSeg, a segmentation algorithm that operates directly on single RNA positions and that does not come with implicit or explicit priors on cell shape. ComSeg is applicable in complex tissues with arbitrary cell shapes. Through comprehensive evaluations on simulated and experimental datasets, we show that ComSeg outperforms existing state-of-the-art methods for in-situ single-cell RNA profiling and in-situ cell type calling. ComSeg is available as a documented and open source pip package at https://github.com/fish-quant/ComSeg .

Nintedanib Mitigates Radiation-Induced Pulmonary Fibrosis by Suppressing Epithelial Cell Inflammatory Response and Inhibiting Fibroblast-to-Myofibroblast Transition

Radiation-induced pulmonary fibrosis (RIPF) represents a serious complication observed in individuals undergoing thoracic radiation therapy. Currently, effective interventions for RIPF are unavailable. Prior research has demonstrated that nintedanib, a Food and Drug Administration (FDA)-approved anti-fibrotic agent for idiopathic pulmonary fibrosis, exerts therapeutic effects on chronic fibrosing interstitial lung disease. This research aimed to investigate the anti-fibrotic influences of nintedanib on RIPF and reveal the fundamental mechanisms. To assess its therapeutic impact, a mouse model of RIPF was established. The process involved nintedanib administration at various time points, both prior to and following thoracic radiation. In the RIPF mouse model, an assessment was conducted on survival rates, body weight, computed tomography features, histological parameters, and changes in gene expression. In vitro experiments were performed to discover the mechanism underlying the therapeutic impact of nintedanib on RIPF. Treatment with nintedanib, administered either two days prior or four weeks after thoracic radiation, significantly alleviated lung pathological changes, suppressed collagen deposition, and improved the overall health status of the mice. Additionally, nintedanib demonstrated significant mitigation of radiation-induced inflammatory responses in epithelial cells by inhibiting the PI3K/AKT and MAPK signaling pathways. Furthermore, nintedanib substantially inhibited fibroblast-to-myofibroblast transition by suppressing the TGF-β/Smad and PI3K/AKT/mTOR signaling pathways. These findings suggest that nintedanib exerts preventive and therapeutic effects on RIPF by modulating multiple targets instead of a single anti-fibrotic pathway and encourage the further clinical trials to determine the efficacy of nintedanib in patients with RIPF.

A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of genomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Furthermore, we propose that bridging the gap between computational and wet lab scientists through user-friendly web-based platforms is needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

Nicaraven attenuates the acquired radioresistance of established tumors in mouse models via PARP inhibition

Nicaraven has been reported to inhibit the activity of poly (ADP-ribose) polymerase (PARP). In this study, we investigated the probable ability of nicaraven to attenuate cancer radioresistance during fractionated radiotherapy. Tumor models were established in C57BL/6 mice and BALB/c nude mice by subcutaneous injection of Lewis mouse lung carcinoma cancer cells and A549 human lung cancer cells, respectively. When the tumors had grown to approximately 100 mm3, we initiated fractionated radiotherapy. Nicaraven or saline was administered immediately after each irradiation exposure. Compared to saline treatment, nicaraven administration significantly induced gamma-H2AX foci formation and cell apoptosis in tumors at 1 or 3 days after an additional challenge exposure to 10 Gy and inhibited tumor growth during the short-term follow-up period, suggesting increased radiosensitivity of cancer cells. Moreover, the expression of PARP in tumor tissue was decreased by nicaraven administration. Our data suggest that nicaraven likely attenuates the acquired radioresistance of cancers through PARP inhibition.

Characterisation of quantitative imaging biomarkers for inflammatory and fibrotic radiation-induced lung injuries using preclinical radiomics

BACKGROUND AND PURPOSE

Radiomics is a rapidly evolving area of research that uses medical images to develop prognostic and predictive imaging biomarkers. In this study, we aimed to identify radiomics features correlated with longitudinal biomarkers in preclinical models of acute inflammatory and late fibrotic phenotypes following irradiation.

MATERIALS AND METHODS

Female C3H/HeN and C57BL6 mice were irradiated with 20 Gy targeting the upper lobe of the right lung under cone-beam computed tomography (CBCT) image-guidance. Blood samples and lung tissue were collected at baseline, weeks 1, 10 & 30 to assess changes in serum cytokines and histological biomarkers. The right lung was segmented on longitudinal CBCT scans using ITK-SNAP. Unfiltered and filtered (wavelet) radiomics features (n = 842) were extracted using PyRadiomics. Longitudinal changes were assessed by delta analysis and principal component analysis (PCA) was used to remove redundancy and identify clustering. Prediction of acute (week 1) and late responses (weeks 20 & 30) was performed through deep learning using the Random Forest Classifier (RFC) model.

RESULTS

Radiomics features were identified that correlated with inflammatory and fibrotic phenotypes. Predictive features for fibrosis were detected from PCA at 10 weeks yet overt tissue density was not detectable until 30 weeks. RFC prediction models trained on 5 features were created for inflammation (AUC 0.88), early-detection of fibrosis (AUC 0.79) and established fibrosis (AUC 0.96).

CONCLUSIONS

This study demonstrates the application of deep learning radiomics to establish predictive models of acute and late lung injury. This approach supports the wider application of radiomics as a non-invasive tool for detection of radiation-induced lung complications.

The AsiDNA™ decoy mimicking DSBs protects the normal tissue from radiation toxicity through a DNA-PK/p53/p21-dependent G1/S arrest

AsiDNA™, a cholesterol-coupled oligonucleotide mimicking double-stranded DNA breaks, was developed to sensitize tumour cells to radio- and chemotherapy. This drug acts as a decoy hijacking the DNA damage response. Previous studies have demonstrated that standalone AsiDNA™ administration is well tolerated with no additional adverse effects when combined with chemo- and/or radiotherapy. The lack of normal tissue complication encouraged further examination into the role of AsiDNA™ in normal cells. This research demonstrates the radioprotective properties of AsiDNA™. In vitro, AsiDNA™ induces a DNA-PK/p53/p21-dependent G1/S arrest in normal epithelial cells and fibroblasts that is absent in p53 deficient and proficient tumour cells. This cell cycle arrest improved survival after irradiation only in p53 proficient normal cells. Combined administration of AsiDNA™ with conventional radiotherapy in mouse models of late and early radiation toxicity resulted in decreased onset of lung fibrosis and increased intestinal crypt survival. Similar results were observed following FLASH radiotherapy in standalone or combined with AsiDNA™. Mechanisms comparable to those identified in vitro were detected both in vivo, in the intestine and ex vivo, in precision cut lung slices. Collectively, the results suggest that AsiDNA™ can partially protect healthy tissues from radiation toxicity by triggering a G1/S arrest in normal cells.

Early, non-invasive detection of radiation-induced lung injury using PET/CT by targeting CXCR4

PURPOSE

Radiation-induced lung injury (RILI) is a severe side effect of radiotherapy (RT) for thoracic malignancies and we currently lack established methods for the early detection of RILI. In this study, we synthesized a new tracer, [18F]AlF-NOTA-QHY-04, targeting C-X-C-chemokine-receptor-type-4 (CXCR4) and investigated its feasibility to detect RILI.

METHODS

An RILI rat model was constructed and scanned with [18F]AlF-NOTA-QHY-04 PET/CT and [18F]FDG PET/CT periodically after RT. Dynamic, blocking, autoradiography, and histopathological studies were performed on the day of peak uptake. Fourteen patients with radiation pneumonia, developed during or after thoracic RT, were subjected to PET scan using [18F]AlF-NOTA-QHY-04.

RESULTS

The yield of [18F]AlF-NOTA-QHY-04 was 28.5-43.2%, and the specific activity was 27-33 GBq/μmol. [18F]AlF-NOTA-QHY-04 was mainly excreted through the kidney. Significant increased [18F]AlF-NOTA-QHY-04 uptake in the irradiated lung compared with that in the normal lung in the RILI model was observed on day 6 post-RT and peaked on day 14 post-RT, whereas no apparent uptake of [18F]FDG was shown on days 7 and 15 post-RT. MicroCT imaging did not show pneumonia until 42 days post-RT. Significant intense [18F]AlF-NOTA-QHY-04 uptake was confirmed by autoradiography. Immunofluorescence staining demonstrated expression of CXCR4 was significantly increased in the irradiated lung tissue, which correlated with results obtained from hematoxylin-eosin and Masson's trichrome staining. In 14 patients with radiation pneumonia, maximum standardized uptake values (SUVmax) were significantly higher in the irradiated lung compared with those in the normal lung. SUVmax of patients with grade 2 RILI was significantly higher than that of patients with grade 1 RILI.

CONCLUSION

This study indicated that [18F]AlF-NOTA-QHY-04 PET/CT imaging can detect RILI non-invasively and earlier than [18F]FDG PET/CT in a rat model. Clinical studies verified its feasibility, suggesting the clinical potential of [18F]AlF-NOTA-QHY-04 as a PET/CT tracer for early monitoring of RILI.

[Radiation-induced pulmonary fibrosis: New potential targets]

Radiation-induced pulmonary fibrosis (RIPF) is one of the major and late complications of radiotherapy (RT) with an average incidence rate between 16 and 28% after RT. RIPF significantly affects the function of the affected tissues/organs as well as the quality of life and survival of patients. The process of radiation fibrogenesis is initiated by a very complex signaling network that involves several cellular and molecular factors and the development of effective treatments relies on a better understanding of the involved mechanisms. Despite a major advance in the field, to date there is no clinical treatment that has really shown efficacy in the prevention or treatment of RIPF. In the present review, we will discuss potential new therapeutic avenues that could effectively treat RIPF.