Dose- and time-dependent changes in gene expression in human glioma cells after low radiation doses

Radiation-Induced Alterations in the Recurrent Glioblastoma Microenvironment: Therapeutic Implications

Glioblastoma (GBM) is uniformly fatal with a median survival of just over 1 year, despite best available treatment including radiotherapy (RT). Impacts of prior brain RT on recurrent tumors are poorly understood, though increasing evidence suggests RT-induced changes in the brain microenvironment contribute to recurrent GBM aggressiveness. The tumor microenvironment impacts malignant cells directly and indirectly through stromal cells that support tumor growth. Changes in extracellular matrix (ECM), abnormal vasculature, hypoxia, and inflammation have been reported to promote tumor aggressiveness that could be exacerbated by prior RT. Prior radiation may have long-term impacts on microglia and brain-infiltrating monocytes, leading to lasting alterations in cytokine signaling and ECM. Tumor-promoting CNS injury responses are recapitulated in the tumor microenvironment and augmented following prior radiation, impacting cell phenotype, proliferation, and infiltration in the CNS. Since RT is vital to GBM management, but substantially alters the tumor microenvironment, we here review challenges, knowledge gaps, and therapeutic opportunities relevant to targeting pro-tumorigenic features of the GBM microenvironment. We suggest that insights from RT-induced changes in the tumor microenvironment may provide opportunities to target mechanisms, such as cellular senescence, that may promote GBM aggressiveness amplified in previously radiated microenvironment.

Radiation-induced alternative transcripts as detected in total and polysome-bound mRNA

Alternative splicing is a critical event in the posttranscriptional regulation of gene expression. To investigate whether this process influences radiation-induced gene expression we defined the effects of ionizing radiation on the generation of alternative transcripts in total cellular mRNA (the transcriptome) and polysome-bound mRNA (the translatome) of the human glioblastoma stem-like cell line NSC11. For these studies, RNA-Seq profiles from control and irradiated cells were compared using the program SpliceSeq to identify transcripts and splice variations induced by radiation. As compared to the transcriptome (total RNA) of untreated cells, the radiation-induced transcriptome contained 92 splice events suggesting that radiation induced alternative splicing. As compared to the translatome (polysome-bound RNA) of untreated cells, the radiation-induced translatome contained 280 splice events of which only 24 were overlapping with the radiation-induced transcriptome. These results suggest that radiation not only modifies alternative splicing of precursor mRNA, but also results in the selective association of existing mRNA isoforms with polysomes. Comparison of radiation-induced alternative transcripts to radiation-induced gene expression in total RNA revealed little overlap (about 3%). In contrast, in the radiation-induced translatome, about 38% of the induced alternative transcripts corresponded to genes whose expression level was affected in the translatome. This study suggests that whereas radiation induces alternate splicing, the alternative transcripts present at the time of irradiation may play a role in the radiation-induced translational control of gene expression and thus cellular radioresponse.

Transcript Analysis for Internal Biodosimetry Using Peripheral Blood from Neuroblastoma Patients Treated with (131)I-mIBG, a Targeted Radionuclide

Calculating internal dose from therapeutic radionuclides currently relies on estimates made from multiple radiation exposure measurements, converted to absorbed dose in specific organs using the Medical Internal Radiation Dose (MIRD) schema. As an alternative biodosimetric approach, we utilized gene expression analysis of whole blood from patients receiving targeted radiotherapy. Collected blood from patients with relapsed or refractory neuroblastoma who received (131)I-labeled metaiodobenzylguanidine ((131)I-mIBG) at the University of California San Francisco (UCSF) was used to compare calculated internal dose with the modulation of chosen gene expression. A total of 40 patients, median age 9 years, had blood drawn at baseline, 72 and 96 h after (131)I-mIBG infusion. Whole-body absorbed dose was calculated for each patient based on the cumulated activity determined from injected mIBG activity and patient-specific time-activity curves combined with (131)I whole-body S factors. We then assessed transcripts that were the most significant for describing the mixed therapeutic treatments over time using real-time polymerase chain reaction (RT-PCR). Modulation was evaluated statistically using multiple regression analysis for data at 0, 72 and 96 h. A total of 10 genes were analyzed across 40 patients: CDKN1A; FDXR; GADD45A; BCLXL; STAT5B; BAX; BCL2; DDB2; XPC; and MDM2. Six genes were significantly modulated upon exposure to (131)I-mIBG at 72 h, as well as at 96 h. Four genes varied significantly with absorbed dose when controlling for time. A gene expression biodosimetry model was developed to predict absorbed dose based on modulation of gene transcripts within whole blood. Three transcripts explained over 98% of the variance in the modulation of gene expression over the 96 h (CDKN1A, BAX and DDB2). To our knowledge, this is a novel study, which uses whole blood collected from patients treated with a radiopharmaceutical, to characterize biomarkers that may be useful for biodosimetry. Our data indicate that transcripts, which have been previously identified as biomarkers of external exposures in ex vivo whole blood and in vivo radiotherapy patients, are also good early indicators of internal exposure. However, for internal sources of radiation, the biokinetics and physical decay of the radionuclide strongly influence the gene expression.

Polysome Profiling Links Translational Control to the Radioresponse of Glioblastoma Stem-like Cells

Changes in polysome-bound mRNA (translatome) are correlated closely with changes in the proteome in cells. Therefore, to better understand the processes mediating the response of glioblastoma to ionizing radiation (IR), we used polysome profiling to define the IR-induced translatomes of a set of human glioblastoma stem-like cell (GSC) lines. Although cell line specificity accounted for the largest proportion of genes within each translatome, there were also genes that were common to the GSC lines. In particular, analyses of the IR-induced common translatome identified components of the DNA damage response, consistent with a role for the translational control of gene expression in cellular radioresponse. Moreover, translatome analyses suggested that IR enhanced cap-dependent translation processes, an effect corroborated by the finding of increased eIF4F-cap complex formation detected after irradiation in all GSC lines. Translatome analyses also predicted that Golgi function was affected by IR. Accordingly, Golgi dispersal was detected after irradiation of each of the GSC lines. In addition to the common responses seen, translatome analyses predicted cell line-specific changes in mitochondria, as substantiated by changes in mitochondrial mass and DNA content. Together, these results suggest that analysis of radiation-induced translatomes can provide new molecular insights concerning the radiation response of cancer cells. More specifically, they suggest that the translational control of gene expression may provide a source of molecular targets for glioblastoma radiosensitization. Cancer Res; 76(10); 3078-87. ©2016 AACR.

Identification of gene expression biomarkers for predicting radiation exposure

A need for more accurate and reliable radiation dosimetry has become increasingly important due to the possibility of a large-scale radiation emergency resulting from terrorism or nuclear accidents. Although traditional approaches provide accurate measurements, such methods usually require tedious effort and at least two days to complete. Therefore, we provide a new method for rapid prediction of radiation exposure. Eleven microarray datasets were classified into two groups based on their radiation doses and utilized as the training samples. For the two groups, Student's t-tests and resampling tests were used to identify biomarkers, and their gene expression ratios were used to develop a prediction model. The performance of the model was evaluated in four independent datasets, and Ingenuity pathway analysis was performed to characterize the associated biological functions. Our meta-analysis identified 29 biomarkers, showing approximately 90% and 80% accuracy in the training and validation samples. Furthermore, the 29 genes significantly participated in the regulation of cell cycle, and 19 of them are regulated by three well-known radiation-modulated transcription factors: TP53, FOXM1 and ERBB2. In conclusion, this study demonstrates a reliable method for identifying biomarkers across independent studies and high and reproducible prediction accuracy was demonstrated in both internal and external datasets.

mRNA Expression Profiles for Prostate Cancer following Fractionated Irradiation Are Influenced by p53 Status

We assessed changes in cell lines of varying p53 status after various fractionation regimens to determine if p53 influences gene expression and if multifractionated (MF) irradiation can induce molecular pathway changes. LNCaP (p53 wild-type), PC3 (p53 null), and DU145 (p53 mutant) prostate carcinoma cells received 5 and 10 Gy as single-dose (SD) or MF (0.5 Gy x 10, 1 Gy x 10, and 2 Gy x 5) irradiation to simulate hypofractionated and conventionally fractionated prostate radiotherapies, respectively. mRNA analysis revealed 978 LNCaP genes differentially expressed (greater than two-fold change, P < .05) after irradiation. Most were altered with SD (69%) and downregulated (75%). Fewer PC3 (343) and DU145 (116) genes were induced, with most upregulated (87%, 89%) and altered with MF irradiation. Gene ontology revealed immune response and interferon genes most prominently expressed after irradiation in PC3 and DU145. Cell cycle regulatory (P = 9.23 x 10(-73), 14.2% of altered genes, nearly universally downregulated) and DNA replication/repair (P = 6.86 x 10(-30)) genes were most prominent in LNCaP. Stress response and proliferation genes were altered in all cell lines. p53-activated genes were only induced in LNCaP. Differences in gene expression exist between cell lines and after varying irradiation regimens that are p53 dependent. As the duration of changes is ≥24 hours, it may be possible to use radiation-inducible targeted therapy to enhance the efficacy of molecular targeted agents.

Identification of radiation-induced expression changes in nonimmortalized human T cells

In the event of a radiation accident or attack, it will be imperative to quickly assess the amount of radiation exposure to accurately triage victims for appropriate care. RNA-based radiation dosimetry assays offer the potential to rapidly screen thousands of individuals in an efficient and cost-effective manner. However, prior to the development of these assays, it will be critical to identify those genes that will be most useful to delineate different radiation doses. Using global expression profiling, we examined expression changes in nonimmortalized T cells across a wide range of doses (0.15-12 Gy). Because many radiation responses are highly dependent on time, expression changes were examined at three different times (3, 8, and 24 h). Analyses identified 61, 512 and 1310 genes with significant linear dose-dependent expression changes at 3, 8 and 24 h, respectively. Using a stepwise regression procedure, a model was developed to estimate in vitro radiation exposures using the expression of three genes (CDKN1A, PSRC1 and TNFSF4) and validated in an independent test set with 86% accuracy. These findings suggest that RNA-based expression assays for a small subset of genes can be employed to develop clinical biodosimetry assays to be used in assessments of radiation exposure and toxicity.

Fractionated radiation therapy can induce a molecular profile for therapeutic targeting

To examine the possibility of using fractionated radiation in a unique way with molecular targeted therapy, gene expression profiles of prostate carcinoma cells treated with 10 Gy radiation administered either as a single dose or as fractions of 2 Gy × 5 and 1 Gy × 10 were examined by microarray analysis. Compared to the single dose, the fractionated irradiation resulted in significant increases in differentially expressed genes in both cell lines, with more robust changes in PC3 cells than in DU145 cells. The differentially expressed genes (>twofold change; P < 0.05) were clustered and their ontological annotations evaluated. In PC3 cells genes regulating immune and stress response, cell cycle and apoptosis were significantly up-regulated by multifractionated radiation compared to single-dose radiation. Ingenuity Pathway Analysis (IPA) of the differentially expressed genes revealed that immune response and cardiovascular genes were in the top functional category in PC3 cells and cell-to-cell signaling in DU145 cells. RT-PCR analysis showed that a flexure point for gene expression occurred at the 6th-8th fraction and AKT inhibitor perifosine produced enhanced cell killing after 1 Gy × 8 fractionated radiation in PC3 and DU145 cells compared to single dose. This study suggests that fractionated radiation may be a uniquely exploitable, non-oncogene-addiction stress pathway for molecular therapeutic targeting.

Distinct signaling pathways after higher or lower doses of radiation in three closely related human lymphoblast cell lines

PURPOSE

The tumor suppressor p53 plays an essential role in cellular responses to DNA damage caused by ionizing radiation; therefore, this study aims to further explore the role that p53 plays at different doses of radiation.

MATERIALS AND METHODS

The global cellular responses to higher-dose (10 Gy) and lower dose (iso-survival dose, i.e., the respective D0 levels) radiation were analyzed using microarrays in three human lymphoblast cell lines with different p53 status: TK6 (wild-type p53), NH32 (p53-null), and WTK1 (mutant p53). Total RNAs were extracted from cells harvested at 0, 1, 3, 6, 9, and 24 h after higher and lower dose radiation exposures. Template-based clustering, hierarchical clustering, and principle component analysis were applied to examine the transcriptional profiles.

RESULTS

Differential expression profiles between 10 Gy and iso-survival radiation in cells with different p53 status were observed. Moreover, distinct gene expression patterns were exhibited among these three cells after 10 Gy radiation treatment, but similar transcriptional responses were observed in TK6 and NH32 cells treated with iso-survival radiation.

CONCLUSIONS

After 10 Gy radiation exposure, the p53 signaling pathway played an important role in TK6, whereas the NFkB signaling pathway appeared to replace the role of p53 in WTK1. In contrast, after iso-survival radiation treatment, E2F4 seemed to play a dominant role independent of p53 status. This study dissected the impacts of p53, NFkB and E2F4 in response to higher or lower doses of gamma-irradiation.