GDF-15 gene expression alterations in human lymphoblastoid cells and peripheral blood lymphocytes following exposure to ionizing radiation

Targeted lipidomics-based study of radiation-induced metabolite profiles changes in plasma of total body irradiation cases

PURPOSE

Lipidomics is an important tool for triaging exposed individuals, and helps early adoption of prevention and control strategies. The purpose of this study was to screen significantly perturbed lipids between pre- and post-irradiation of human plasma samples after total body irradiation (TBI) and explore potential radiation biomarkers for early radiation classification.

METHODS

Plasma samples were collected before and after irradiation from 22 hospitalized cases of acute myeloid leukemia (AML) prepared for bone marrow transplantation. Acute total-body γ irradiation was performed at doses of 0, 4, 8, and 12 Gy. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) with multiple reaction monitoring (MRM) method was utilized. Self-paired studies before and after irradiation were performed to screen potential lipid categorization markers and markers of dose-response relationships for radiation perturbation in humans. Based on the screened potential markers, a human TBI dose estimation model was developed.

RESULTS

In total, 426 individual lipids from 14 major classes were quantified and 152 potential biomarkers with categorical characteristics were screened. A total of 80 lipids (32 TGs, 29 SMs, 9 FAs, 5 CEs, 5 PIs) were upregulated at 4 Gy, and a total of 91 lipids (39 SMs, 18 TGs, 15 HexCers, 7 CEs, 6 Cers, 3 LacCers, 2 LPEs, 1 PI) were upregulated at 12 Gy. Comparison of the ROC curves between the non-exposed and exposed groups at different doses showed AUC values ranging from 0.807 to 0.876. The metabolic pathways of potential lipid markers are mainly sphingolipid and glycerolipid metabolism, unsaturated fatty acid biosynthesis, fatty acid degradation and biosynthesis. Among the 13 dose-dependent radiosensitive lipids, CE (20:5), CE (18:1) and PI (18:2/18:2) were gradually incorporated into the TBI dose estimation model.

CONCLUSION

This study suggested that it was feasible to acquire quantitative lipid biomarker panels using targeted lipidomics platforms for rapid, high-throughput triage. Lipidomics strategies for radiation biodosimetry in humans were established with lipid biomarkers with good dose-response relationship.

Microarray analysis of hub genes, non-coding RNAs and pathways in lung after whole body irradiation in a mouse model

PURPOSE

Previous research has highlighted the impact of radiation damage, with cancer patients developing acute disorders including radiation induced pneumonitis or chronic disorders including pulmonary fibrosis months after radiation therapy ends. We sought to discover biomarkers that predict these injuries and develop treatments that mitigate this damage and improve quality of life.

MATERIALS AND METHODS

Six- to eight-week-old female C57BL/6 mice received 1, 2, 4, 8, 12 Gy or sham whole body irradiation. Animals were euthanized 48 h post exposure and lungs removed, snap frozen and underwent RNA isolation. Microarray analysis was performed to determine dysregulation of messenger RNA (mRNA), microRNA (miRNA), and long non-coding RNA (lncRNA) after radiation injury.

RESULTS

We observed sustained dysregulation of specific RNA markers including: mRNAs, lncRNAs, and miRNAs across all doses. We also identified significantly upregulated genes that can indicate high dose exposure, including Cpt1c, Pdk4, Gdf15, and Eda2r, which are markers of senescence and fibrosis. Only three miRNAs were significantly dysregulated across all radiation doses: miRNA-142-3p and miRNA-142-5p were downregulated and miRNA-34a-5p was upregulated. IPA analysis predicted inhibition of several molecular pathways with increasing doses of radiation, including: T cell development, Quantity of leukocytes, Quantity of lymphocytes, and Cell viability.

CONCLUSIONS

These RNA biomarkers might be highly relevant in the development of treatments and in predicting normal tissue injury in patients undergoing radiation treatment. We are conducting further experiments in our laboratory, which includes a human lung-on-a-chip model, to develop a decision tree model using RNA biomarkers.

Role of blood derived cell fractions, temperature and sample transport on gene expression-based biological dosimetry

PURPOSE

For triage purposes following a nuclear accident or a terrorist event, gene expression biomarkers in blood have been demonstrated to be good bioindicators of ionizing radiation (IR) exposure and can be used to assess the dose received by exposed individuals. Many IR-sensitive genes are regulated by the DNA damage response pathway, and modulators of this pathway could potentially affect their expression level and therefore alter accurate dose estimations. In the present study, we addressed the potential influence of temperature, sample transport conditions and the blood cell fraction analyzed on the transcriptional response of the following radiation-responsive genes: FDXR, CCNG1, MDM2, PHPT1, APOBEC3H, DDB2, SESN1, P21, PUMA, and GADD45.

MATERIALS AND METHODS

Whole blood from healthy donors was exposed to a 2 Gy X-ray dose with a dose rate of 0.5 Gy/min (output 13 mA, 250 kV peak, 0.2 mA) and incubated for 24 h at either 37, 22, or 4 °C. For mimicking the effect of transport conditions at different temperatures, samples incubated at 37 °C for 24 h were kept at 37, 22 or 4 °C for another 24 h. Comparisons of biomarker responses to IR between white blood cells (WBCs), peripheral blood mononuclear cells (PBMCs) and whole blood were carried out after a 2 Gy X-ray exposure and incubation at 37 °C for 24 hours.

RESULTS

Hypothermic conditions (22 or 4 °C) following irradiation drastically inhibited transcriptional responses to IR exposure. However, sample shipment at different temperatures did not affect gene expression level except for SESN1. The transcriptional response to IR of specific genes depended on the cell fraction used, apart from FDXR, CCNG1, and SESN1.

CONCLUSION

In conclusion, temperature during the incubation period and cell fraction but not the storing conditions during transport can influence the transcriptional response of specific genes. However, FDXR and CCNG1 showed a consistent response under all the different conditions tested demonstrating their reliability as individual biological dosimetry biomarkers.

Systemic modulation of stress and immune parameters in patients treated for prostate adenocarcinoma by intensity-modulated radiation therapy or stereotactic ablative body radiotherapy

Background

In this exploratory study, the impact of local irradiation on systemic changes in stress and immune parameters was investigated in eight patients treated with intensity-modulated radiation therapy (IMRT) or stereotactic ablative body radiotherapy (SABR) for prostate adenocarcinoma to gain deeper insights into how radiotherapy (RT) modulates the immune system.

Patients and methods

RT-qPCR, flow cytometry, metabolomics, and antibody arrays were used to monitor a panel of stress- and immune-related parameters before RT, after the first fraction (SABR) or the first week of treatment (IMRT), after the last fraction, and 3 weeks later in the blood of IMRT (N = 4) or SABR (N = 4) patients. Effect size analysis was used for comparison of results at different timepoints.

Results

Several parameters were found to be differentially modulated in IMRT and SABR patients: the expression of TGFB1, IL1B, and CCL3 genes; the expression of HLA-DR on circulating monocytes; the abundance and ratio of phosphatidylcholine and lysophosphatidylcholine metabolites in plasma. More immune modulators in plasma were modulated during IMRT than SABR, with only two common proteins, namely GDF-15 and Tim‑3.

Conclusion

Locally delivered RT induces systemic modulation of the immune system in prostate adenocarcinoma patients. IMRT and SABR appear to specifically affect distinct immune components.

Electronic supplementary material

The online version of this article (10.1007/s00066-020-01637-5) contains supplementary material, which is available to authorized users.

Towards frailty biomarkers: Candidates from genes and pathways regulated in aging and age-related diseases

OBJECTIVE

Use of the frailty index to measure an accumulation of deficits has been proven a valuable method for identifying elderly people at risk for increased vulnerability, disease, injury, and mortality. However, complementary molecular frailty biomarkers or ideally biomarker panels have not yet been identified. We conducted a systematic search to identify biomarker candidates for a frailty biomarker panel.

METHODS

Gene expression databases were searched (http://genomics.senescence.info/genes including GenAge, AnAge, LongevityMap, CellAge, DrugAge, Digital Aging Atlas) to identify genes regulated in aging, longevity, and age-related diseases with a focus on secreted factors or molecules detectable in body fluids as potential frailty biomarkers. Factors broadly expressed, related to several "hallmark of aging" pathways as well as used or predicted as biomarkers in other disease settings, particularly age-related pathologies, were identified. This set of biomarkers was further expanded according to the expertise and experience of the authors. In the next step, biomarkers were assigned to six "hallmark of aging" pathways, namely (1) inflammation, (2) mitochondria and apoptosis, (3) calcium homeostasis, (4) fibrosis, (5) NMJ (neuromuscular junction) and neurons, (6) cytoskeleton and hormones, or (7) other principles and an extensive literature search was performed for each candidate to explore their potential and priority as frailty biomarkers.

RESULTS

A total of 44 markers were evaluated in the seven categories listed above, and 19 were awarded a high priority score, 22 identified as medium priority and three were low priority. In each category high and medium priority markers were identified.

CONCLUSION

Biomarker panels for frailty would be of high value and better than single markers. Based on our search we would propose a core panel of frailty biomarkers consisting of (1) CXCL10 (C-X-C motif chemokine ligand 10), IL-6 (interleukin 6), CX3CL1 (C-X3-C motif chemokine ligand 1), (2) GDF15 (growth differentiation factor 15), FNDC5 (fibronectin type III domain containing 5), vimentin (VIM), (3) regucalcin (RGN/SMP30), calreticulin, (4) PLAU (plasminogen activator, urokinase), AGT (angiotensinogen), (5) BDNF (brain derived neurotrophic factor), progranulin (PGRN), (6) α-klotho (KL), FGF23 (fibroblast growth factor 23), FGF21, leptin (LEP), (7) miRNA (micro Ribonucleic acid) panel (to be further defined), AHCY (adenosylhomocysteinase) and KRT18 (keratin 18). An expanded panel would also include (1) pentraxin (PTX3), sVCAM/ICAM (soluble vascular cell adhesion molecule 1/Intercellular adhesion molecule 1), defensin α, (2) APP (amyloid beta precursor protein), LDH (lactate dehydrogenase), (3) S100B (S100 calcium binding protein B), (4) TGFβ (transforming growth factor beta), PAI-1 (plasminogen activator inhibitor 1), TGM2 (transglutaminase 2), (5) sRAGE (soluble receptor for advanced glycosylation end products), HMGB1 (high mobility group box 1), C3/C1Q (complement factor 3/1Q), ST2 (Interleukin 1 receptor like 1), agrin (AGRN), (6) IGF-1 (insulin-like growth factor 1), resistin (RETN), adiponectin (ADIPOQ), ghrelin (GHRL), growth hormone (GH), (7) microparticle panel (to be further defined), GpnmB (glycoprotein nonmetastatic melanoma protein B) and lactoferrin (LTF). We believe that these predicted panels need to be experimentally explored in animal models and frail cohorts in order to ascertain their diagnostic, prognostic and therapeutic potential.