Differential radiation response between normal astrocytes and glioma cells revealed by comparative transcriptome analysis

Rapid P-TEFb-dependent transcriptional reorganization underpins the glioma adaptive response to radiotherapy

Dynamic regulation of gene expression is fundamental for cellular adaptation to exogenous stressors. P-TEFb-mediated pause-release of RNA polymerase II (Pol II) is a conserved regulatory mechanism for synchronous transcriptional induction in response to heat shock, but this pro-survival role has not been examined in the applied context of cancer therapy. Using model systems of pediatric high-grade glioma, we show that rapid genome-wide reorganization of active chromatin facilitates P-TEFb-mediated nascent transcriptional induction within hours of exposure to therapeutic ionizing radiation. Concurrent inhibition of P-TEFb disrupts this chromatin reorganization and blunts transcriptional induction, abrogating key adaptive programs such as DNA damage repair and cell cycle regulation. This combination demonstrates a potent, synergistic therapeutic potential agnostic of glioma subtype, leading to a marked induction of tumor cell apoptosis and prolongation of xenograft survival. These studies reveal a central role for P-TEFb underpinning the early adaptive response to radiotherapy, opening avenues for combinatorial treatment in these lethal malignancies.

Rapid PTEFb-dependent transcriptional reorganization underpins the glioma adaptive response to radiotherapy

Dynamic regulation of gene expression is fundamental for cellular adaptation to exogenous stressors. PTEFb-mediated pause-release of RNA polymerase II (Pol II) is a conserved regulatory mechanism for synchronous transcriptional induction in response to heat shock, but this pro-survival role has not been examined in the applied context of cancer therapy. Using model systems of pediatric high-grade glioma, we show that rapid genome-wide reorganization of active chromatin facilitates PTEFb-mediated nascent transcriptional induction within hours of exposure to therapeutic ionizing radiation. Concurrent inhibition of PTEFb disrupts this chromatin reorganization and blunts transcriptional induction, abrogating key adaptive programs such as DNA damage repair and cell cycle regulation. This combination demonstrates a potent, synergistic therapeutic potential agnostic of glioma subtype, leading to a marked induction of tumor cell apoptosis and prolongation of xenograft survival. These studies reveal a central role for PTEFb underpinning the early adaptive response to radiotherapy, opening new avenues for combinatorial treatment in these lethal malignancies.

A novel autophagy-related long non-coding RNAs signature predicting progression-free interval and I-131 therapy benefits in papillary thyroid carcinoma

This study aimed to explore the prognostic and predictive value of autophagy-related lncRNAs in papillary thyroid carcinoma (PTC). The expression data of autophagy-related genes and lncRNAs of the PTC patients were obtained from TCGA database. Autophagy-related-differentially expressed lncRNAs (DElncs) were identified and used to establish the lncRNAs signature predicting patients' progression-free interval (PFI) in the training cohort. Its performance was assessed in the training cohort, validation cohort, and entire cohort. Effects of the signature on I-131 therapy were also explored. We identified 199 autophagy-related-DElncs and constructed a novel six-lncRNAs signature was constructed based on these lncRNAs. This signature had a good predictive performance and was superior to TNM stages and previous clinical risk scores. I-131 therapy was found to be associated with favorable prognosis in patients with high-risk scores but not those with low-risk scores. Gene set enrichment analysis suggested that a series of hallmark gene sets were enriched in the high-risk subgroup. Single-cell RNA sequencing analysis suggested that the lncRNAs were mainly expressed in thyroid cells but not stromal cells. In conclusion, our study constructed a well-performed six-lncRNAs signature to predict PFI and I-131 therapy benefits in PTC.

Mouse models of glioblastoma for the evaluation of novel therapeutic strategies

Glioblastoma (GBM) is an incurable brain tumor with a median survival of approximately 15 months despite an aggressive standard of care that includes surgery, chemotherapy, and ionizing radiation. Mouse models have advanced our understanding of GBM biology and the development of novel therapeutic strategies for GBM patients. However, model selection is crucial when testing developmental therapeutics, and each mouse model of GBM has unique advantages and disadvantages that can influence the validity and translatability of experimental results. To shed light on this process, we discuss the strengths and limitations of 3 types of mouse GBM models in this review: syngeneic models, genetically engineered mouse models, and xenograft models, including traditional xenograft cell lines and patient-derived xenograft models.

Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance

Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learning classifiers. Despite the acknowledged role of tumor metabolism in radiation response, metabolomics data is rarely collected in large multi-omics initiatives such as The Cancer Genome Atlas (TCGA) and consequently omitted from algorithm development. In this study, we circumvent the paucity of personalized metabolomics information by characterizing 915 TCGA patient tumors with genome-scale metabolic Flux Balance Analysis models generated from transcriptomic and genomic datasets. Metabolic biomarkers differentiating radiation-sensitive and -resistant tumors are predicted and experimentally validated, enabling integration of metabolic features with other multi-omics datasets into ensemble-based machine learning classifiers for radiation response. These multi-omics classifiers show improved classification accuracy, identify clinical patient subgroups, and demonstrate the utility of personalized blood-based metabolic biomarkers for radiation sensitivity. The integration of machine learning with genome-scale metabolic modeling represents a significant methodological advancement for identifying prognostic metabolite biomarkers and predicting radiosensitivity for individual patients.

The Irradiated Brain Microenvironment Supports Glioma Stemness and Survival via Astrocyte-Derived Transglutaminase 2

The tumor microenvironment plays an essential role in supporting glioma stemness and radioresistance. Following radiotherapy, recurrent gliomas form in an irradiated microenvironment. Here we report that astrocytes, when pre-irradiated, increase stemness and survival of cocultured glioma cells. Tumor-naïve brains increased reactive astrocytes in response to radiation, and mice subjected to radiation prior to implantation of glioma cells developed more aggressive tumors. Extracellular matrix derived from irradiated astrocytes were found to be a major driver of this phenotype and astrocyte-derived transglutaminase 2 (TGM2) was identified as a promoter of glioma stemness and radioresistance. TGM2 levels increased after radiation in vivo and in recurrent human glioma, and TGM2 inhibitors abrogated glioma stemness and survival. These data suggest that irradiation of the brain results in the formation of a tumor-supportive microenvironment. Therapeutic targeting of radiation-induced, astrocyte-derived extracellular matrix proteins may enhance the efficacy of standard-of-care radiotherapy by reducing stemness in glioma. SIGNIFICANCE: These findings presented here indicate that radiotherapy can result in a tumor-supportive microenvironment, the targeting of which may be necessary to overcome tumor cell therapeutic resistance and recurrence. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/8/2101/F1.large.jpg.

Photon versus proton neurotoxicity: Impact on mitochondrial function and 8-OHdG base-excision repair mechanism in human astrocytes

This study assesses and compares the neurotoxic effects of proton and photon radiation on mitochondrial function and DNA repair capabilities of human astrocytes. Human astrocytes received either proton (0.5 Gy and 3 Gy), photon (0.5 Gy and 3 Gy), or sham-radiation treatment. The mRNA expression level of the DNA repair protein OGG1 was determined via RT-qPCR. The levels of 8-OHdG in the cell media were measured via ELISA. Real-time kinetic analysis of extracellular oxygen consumption rates was performed to assess mitochondrial function. Radiation-induced changes in mitochondrial mass and oxidative activity were assessed using fluorescent imaging with MitoTracker™ Green FM and MitoTracker™ Orange CM-H₂TMRos dyes respectively. PCR was used to quantify the alteration in the mitochondrial DNA content, measured as the mitochondrial to nuclear DNA ratio. A significant increase in mitochondrial mass and levels of reactive oxygen species was observed after radiation treatment. Additionally, real-time PCR analysis indicated a significant depletion of mitochondrial DNA content in the irradiated cells when compared to the control. This was accompanied by a decreased gene expression of the DNA base-excision repair protein OGG1 and reduced clearance of 8-OHdG adducts from the genome. Photon radiation treatment was associated with a more detrimental cellular impact when compared to the same dose of proton radiation. These results are indicative of a radiation-induced dose-dependent decrease in mitochondrial function, an increase in senescence and astrogliosis, and impairment of the DNA repair capabilities in healthy glial cells. Photon irradiation was associated with a more significant disruption in mitochondrial function and base-excision repair mechanisms in vitro in comparison to proton treatment.