Transcriptional Response in Mouse Thyroid Tissue after 211At Administration: Effects of Absorbed Dose, Initial Dose-Rate and Time after Administration

Development of a machine learning framework for radiation biomarker discovery and absorbed dose prediction

Background

Molecular radiation biomarkers are an emerging tool in radiation research with applications for cancer radiotherapy, radiation risk assessment, and even human space travel. However, biomarker screening in genome-wide expression datasets using conventional tools is time-consuming and underlies analyst (human) bias. Machine Learning (ML) methods can improve the sensitivity and specificity of biomarker identification, increase analytical speed, and avoid multicollinearity and human bias.

Aim

To develop a resource-efficient ML framework for radiation biomarker discovery using gene expression data from irradiated normal tissues. Further, to identify biomarker panels predicting radiation dose with tissue specificity.

Methods

A strategic search in the Gene Expression Omnibus database identified a transcriptomic dataset (GSE44762) for normal tissues radiation responses (murine kidney cortex and medulla) suited for biomarker discovery using an ML approach. The dataset was pre-processed in R and separated into train and test data subsets. High computational cost of Genetic Algorithm/k-Nearest Neighbor (GA/KNN) mandated optimization and 13 ML models were tested using the caret package in R. Biomarker performance was evaluated and visualized via Principal Component Analysis (PCA) and dose regression. The novelty of ML-identified biomarker panels was evaluated by literature search.

Results

Caret-based feature selection and ML methods vastly improved processing time over the GA approach. The KNN method yielded overall best performance values on train and test data and was implemented into the framework. The top-ranking genes were Cdkn1a, Gria3, Mdm2 and Plk2 in cortex, and Brf2, Ccng1, Cdkn1a, Ddit4l, and Gria3 in medulla. These candidates successfully categorized dose groups and tissues in PCA. Regression analysis showed that correlation between predicted and true dose was high with R² of 0.97 and 0.99 for cortex and medulla, respectively.

Conclusion

The caret framework is a powerful tool for radiation biomarker discovery optimizing performance with resource-efficiency for broad implementation in the field. The KNN-based approach identified Brf2, Ddit4l, and Gria3 mRNA as novel candidates that have been uncharacterized as radiation biomarkers to date. The biomarker panel showed good performance in dose and tissue separation and dose regression. Further training with larger cohorts is warranted to improve accuracy, especially for lower doses.

Age and sex effects across the blood proteome after ionizing radiation exposure can bias biomarker screening and risk assessment

Molecular biomarkers of ionizing radiation (IR) exposure are a promising new tool in various disciplines: they can give necessary information for adaptive treatment planning in cancer radiotherapy, enable risk projection for radiation-induced survivorship diseases, or facilitate triage and intervention in radiation hazard events. However, radiation biomarker discovery has not yet resolved the most basic features of personalized medicine: age and sex. To overcome this critical bias in biomarker identification, we quantitated age and sex effects and assessed their relevance in the radiation response across the blood proteome. We used high-throughput mass spectrometry on blood plasma collected 24 h after 0.5 Gy total body irradiation (15 MV nominal photon energy) from male and female C57BL/6 N mice at juvenile (7-weeks-old) or adult (18-weeks-old) age. We also assessed sex and strain effects using juvenile male and female BALB/c nude mice. We showed that age and sex created significant effects in the proteomic response regarding both extent and functional quality of IR-induced responses. Furthermore, we found that age and sex effects appeared non-linear and were often end-point specific. Overall, age contributed more to differences in the proteomic response than sex, most notably in immune responses, oxidative stress, and apoptotic cell death. Interestingly, sex effects were pronounced for DNA damage and repair pathways and associated cellular outcome (pro-survival vs. pro-apoptotic). Only one protein (AHSP) was identified as a potential general biomarker candidate across age and sex, while GMNN, REG3B, and SNCA indicated some response similarity across age. This low yield advocated that unisex or uniage biomarker screening approaches are not feasible. In conclusion, age- and sex-specific screening approaches should be implemented as standard protocol to ensure robustness and diagnostic power of biomarker candidates. Bias-free molecular biomarkers are a necessary progression towards personalized medicine and integral for advanced adaptive cancer radiotherapy and risk assessment.

Inter-laboratory comparison of gene expression biodosimetry for protracted radiation exposures as part of the RENEB and EURADOS WG10 2019 exercise

Large-scale radiation emergency scenarios involving protracted low dose rate radiation exposure (e.g. a hidden radioactive source in a train) necessitate the development of high throughput methods for providing rapid individual dose estimates. During the RENEB (Running the European Network of Biodosimetry) 2019 exercise, four EDTA-blood samples were exposed to an Iridium-192 source (1.36 TBq, Tech-Ops 880 Sentinal) at varying distances and geometries. This resulted in protracted doses ranging between 0.2 and 2.4 Gy using dose rates of 1.5-40 mGy/min and exposure times of 1 or 2.5 h. Blood samples were exposed in thermo bottles that maintained temperatures between 39 and 27.7 °C. After exposure, EDTA-blood samples were transferred into PAXGene tubes to preserve RNA. RNA was isolated in one laboratory and aliquots of four blinded RNA were sent to another five teams for dose estimation based on gene expression changes. Using an X-ray machine, samples for two calibration curves (first: constant dose rate of 8.3 mGy/min and 0.5-8 h varying exposure times; second: varying dose rates of 0.5-8.3 mGy/min and 4 h exposure time) were generated for distribution. Assays were run in each laboratory according to locally established protocols using either a microarray platform (one team) or quantitative real-time PCR (qRT-PCR, five teams). The qRT-PCR measurements were highly reproducible with coefficient of variation below 15% in ≥ 75% of measurements resulting in reported dose estimates ranging between 0 and 0.5 Gy in all samples and in all laboratories. Up to twofold reductions in RNA copy numbers per degree Celsius relative to 37 °C were observed. However, when irradiating independent samples equivalent to the blinded samples but increasing the combined exposure and incubation time to 4 h at 37 °C, expected gene expression changes corresponding to the absorbed doses were observed. Clearly, time and an optimal temperature of 37 °C must be allowed for the biological response to manifest as gene expression changes prior to running the gene expression assay. In conclusion, dose reconstructions based on gene expression measurements are highly reproducible across different techniques, protocols and laboratories. Even a radiation dose of 0.25 Gy protracted over 4 h (1 mGy/min) can be identified. These results demonstrate the importance of the incubation conditions and time span between radiation exposure and measurements of gene expression changes when using this method in a field exercise or real emergency situation.

The IRI-DICE hypothesis: ionizing radiation-induced DSBs may have a functional role for non-deterministic responses at low doses

Low-dose ionizing radiation (IR) responses remain an unresolved issue in radiation biology and risk assessment. Accurate knowledge of low-dose responses is important for estimation of normal tissue risk in cancer radiotherapy or health risks from occupational or hazard exposure. Cellular responses to low-dose IR appear diverse and stochastic in nature and to date no model has been proposed to explain the underlying mechanisms. Here, we propose a hypothesis on IR-induced double-strand break (DSB)-induced cis effects (IRI-DICE) and introduce DNA sequence functionality as a submicron-scale target site with functional outcome on gene expression: DSB induction in a certain genetic target site such as promotor, regulatory element, or gene core would lead to changes in transcript expression, which may range from suppression to overexpression depending on which functional element was damaged. The DNA damage recognition and repair machinery depicts threshold behavior requiring a certain number of DSBs for induction. Stochastically distributed persistent disruption of gene expression may explain-in part-the diverse nature of low-dose responses until the repair machinery is initiated at increased absorbed dose. Radiation quality and complexity of DSB lesions are also discussed. Currently, there are no technologies available to irradiate specific genetic sites to test the IRI-DICE hypothesis directly. However, supportive evidence may be achieved by developing a computational model that combines radiation transport codes with a genomic DNA model that includes sequence functionality and transcription to simulate expression changes in an irradiated cell population. To the best of our knowledge, IRI-DICE is the first hypothesis that includes sequence functionality of different genetic elements in the radiation response and provides a model for the diversity of radiation responses in the (very) low dose regimen.

Preclinical Evaluation of Radiation-Induced Toxicity in Targeted Alpha Therapy Using [211At] NaAt in Mice: A Revisit

We recently reported the dose-dependent therapeutic effect of ²¹¹At-NaAt in differentiated thyroid cancer xenograft models. In the present study, we evaluated the radiation-induced toxicity of ²¹¹At-NaAt using detailed hematological, biochemical, and histological analyses. Biodistribution of ²¹¹At-NaAt was measured in normal ICR mice (n = 12), absorbed doses in the major organs were calculated. Groups of ICR mice (n = 60) were injected with 0.1 MBq or 1 MBq of ²¹¹At-NaAt, using saline as the control group (n = 30). Body weight and food intake were followed up for 60 days. Blood cell counts and serum level of biochemical parameters were measured 3, 7, 15, 29, 60 days after injection. Histological analyses of the major organs with hematoxylin and eosin staining were performed. Biodistribution study revealed a high-absorbed dose in the thyroid gland, stomach, bladder, heart, lungs, spleen, kidneys, and testis. The 0.1 MBq group showed no abnormalities. The 1 MBq group showed decreased body weight and food intake. Histological analysis showed atrophy and fibrosis in the thyroid gland, a transient hypospermatogenesis in the testis on day 29 was found in one mouse. Hematological toxicity was mild and transient. The total cholesterol, albumin, and total protein increased with no signs of recovery, which was considered to be caused by hypothyroidism. High-dose administration of ²¹¹At-NaAt showed transient toxicity in the white blood cells and testis without severe hematological or renal toxicity, suggesting its tolerable safety as targeted alpha-therapy for differentiated thyroid cancer in the 1 MBq group.

Transcriptional effects of 177Lu-octreotate therapy using a priming treatment schedule on GOT1 tumor in nude mice

BACKGROUND

¹⁷⁷Lu-octreotate is used for therapy of somatostatin receptor expressing neuroendocrine tumors with promising results, although complete tumor remission is rarely seen. Previous studies on nude mice bearing the human small intestine neuroendocrine tumor, GOT1, have shown that a priming injection of ¹⁷⁷Lu-octreotate 24 h before the main injection of ¹⁷⁷Lu-octreotate resulted in higher ¹⁷⁷Lu concentration in tumor, resulting in increased absorbed dose, volume reduction, and time to regrowth. To our knowledge, the cellular effects of a priming treatment schedule have not yet been studied. The aim of this study was to identify transcriptional changes contributing to the enhanced therapeutic response of GOT1 tumors in nude mice to ¹⁷⁷Lu-octreotate therapy with priming, compared with non-curative monotherapy.

RESULTS

RNA microarray analysis was performed on tumor samples from GOT1-bearing BALB/c nude mice treated with a 5 MBq priming injection of ¹⁷⁷Lu-octreotate followed by a second injection of 10 MBq of ¹⁷⁷Lu-octreotate after 24 h and killed after 1, 3, 7, and 41 days after the last injection. Administered activity amounts were chosen to be non-curative, in order to facilitate the study of tumor regression and regrowth. Differentially regulated transcripts (RNA samples from treated vs. untreated animals) were identified (change ≥ 1.5-fold; adjusted p value < 0.01) using Nexus Expression 3.0. Analysis of the biological effects of transcriptional regulation was performed using the Gene Ontology database and Ingenuity Pathway Analysis. Transcriptional analysis of the tumors revealed two stages of pathway regulation for the priming schedule (up to 1 week and around 1 month) which differed distinctly from cellular responses observed after monotherapy. Induction of cell cycle arrest and apoptotic pathways (intrinsic and extrinsic) was found at early time points after treatment start, while downregulation of pro-proliferative genes were found at a late time point.

CONCLUSIONS

The present study indicates increased cellular stress responses in the tumors treated with a priming treatment schedule compared with those seen after conventional ¹⁷⁷Lu-octreotate monotherapy, resulting in a more profound initiation of cell cycle arrest followed by apoptosis, as well as effects on PI3K/AKT-signaling and unfolded protein response.

Deconvolution of expression microarray data reveals 131I-induced responses otherwise undetected in thyroid tissue

High-throughput gene expression analysis is increasingly used in radiation research for discovery of damage-related or absorbed dose-dependent biomarkers. In tissue samples, cell type-specific responses can be masked in expression data due to mixed cell populations which can preclude biomarker discovery. In this study, we deconvolved microarray data from thyroid tissue in order to assess possible bias from mixed cell type data. Transcript expression data [GSE66303] from mouse thyroid that received 5.9 Gy from ¹³¹I over 24 h (or 0 Gy from mock treatment) were deconvolved by cell frequency of follicular cells and C-cells using csSAM and R and processed with Nexus Expression. Literature-based signature genes were used to assess the relative impact from ionizing radiation (IR) or thyroid hormones (TH). Regulation of cellular functions was inferred by enriched biological processes according to Gene Ontology terms. We found that deconvolution increased the detection rate of significantly regulated transcripts including the biomarker candidate family of kallikrein transcripts. Detection of IR-associated and TH-responding signature genes was also increased in deconvolved data, while the dominating trend of TH-responding genes was reproduced. Importantly, responses in biological processes for DNA integrity, gene expression integrity, and cellular stress were not detected in convoluted data–which was in disagreement with expected dose-response relationships–but upon deconvolution in follicular cells and C-cells. In conclusion, previously reported trends of ¹³¹I-induced transcriptional responses in thyroid were reproduced with deconvolved data and usually with a higher detection rate. Deconvolution also resolved an issue with detecting damage and stress responses in enriched data, and may reduce false negatives in other contexts as well. These findings indicate that deconvolution can optimize microarray data analysis of heterogeneous sample material for biomarker screening or other clinical applications.

Time-dependent transcriptional response of GOT1 human small intestine neuroendocrine tumor after 177Lu[Lu]-octreotate therapy

INTRODUCTION

Patients with neuroendocrine tumors expressing somatostatin receptors are often treated with ¹⁷⁷Lu[Lu]-octreotate. Despite being highly effective in animal models, ¹⁷⁷Lu[Lu]-octreotate-based therapies in the clinical setting can be optimized further. The aims of the study were to identify and elucidate possible optimization venues for ¹⁷⁷Lu[Lu]-octreotate tumor therapy by characterizing transcriptional responses in the GOT1 small intestine neuroendocrine tumor model in nude mice.

METHODS

GOT1-bearing female BALB/c nude mice were intravenously injected with 15 MBq ¹⁷⁷Lu[Lu]-octreotate (non-curative amount) or mock-treated with saline solution. Animals were killed 1, 3, 7 or 41 d after injection. Total RNA was extracted from the tumor samples and profiled using Illumina microarray expression analysis. Differentially expressed genes were identified (treated vs. control) and pathway analysis was performed.

RESULTS

Distribution of differentially expressed transcripts indicated a time-dependent treatment response in GOT1 tumors after ¹⁷⁷Lu[Lu]-octreotate administration. Regulation of CDKN1A, BCAT1 and PAM at 1 d after injection was compatible with growth arrest as the initial response to treatment. Upregulation of APOE and BAX at 3 d, and ADORA2A, BNIP3, BNIP3L and HSPB1 at 41 d after injection suggests first activation and then inhibition of the intrinsic apoptotic pathway during tumor regression and regrowth, respectively.

CONCLUSION

Transcriptional analysis showed radiation-induced apoptosis as an early response after ¹⁷⁷Lu[Lu]-octreotate administration, followed by pro-survival transcriptional changes in the tumor during the regrowth phase. Time-dependent changes in cell cycle and apoptosis-related processes suggest different time points after radionuclide therapy when tumor cells may be more susceptible to additional treatment, highlighting the importance of timing when administering multiple therapeutic agents.

Transcriptional response to 131I exposure of rat thyroid gland

Humans are exposed to ¹³¹I in medical diagnostics and treatment but also from nuclear accidents, and better knowledge of the molecular response in thyroid is needed. The aim of the study was to examine the transcriptional response in thyroid tissue 24 h after ¹³¹I administration in rats. The exposure levels were chosen to simulate both the clinical situation and the case of nuclear fallout. Thirty-six male rats were i.v. injected with 0–4700 kBq ¹³¹I, and killed at 24 h after injection (D_thyroid = 0.0058–3.0 Gy). Total RNA was extracted from individual thyroid tissue samples and mRNA levels were determined using oligonucleotide microarray technique. Differentially expressed transcripts were determined using Nexus Expression 3.0. Hierarchical clustering was performed in the R statistical computing environment. Pathway analysis was performed using the Ingenuity Pathway Analysis tool and the Gene Ontology database. T4 and TSH plasma concentrations were measured using ELISA. Totally, 429 differentially regulated transcripts were identified. Downregulation of thyroid hormone biosynthesis associated genes (e.g. thyroglobulin, thyroid peroxidase, the sodium-iodine symporter) was identified in some groups, and an impact on thyroid function was supported by the pathway analysis. Recurring downregulation of Dbp and Slc47a2 was found. Dbp exhibited a pattern with monotonous reduction of downregulation with absorbed dose at 0.0058–0.22 Gy. T4 plasma levels were increased and decreased in rats whose thyroids were exposed to 0.057 and 0.22 Gy, respectively. Different amounts of injected ¹³¹I gave distinct transcriptional responses in the rat thyroid. Transcriptional response related to thyroid function and changes in T4 plasma levels were found already at very low absorbed doses to thyroid.

Microarray Studies on 211At Administration in BALB/c Nude Mice Indicate Systemic Effects on Transcriptional Regulation in Nonthyroid Tissues

Targeted α-therapy is a promising treatment option for various types of malignant tumors. Radiolabeled cancer-seeking agents, however, undergo degradation, resulting in a certain percentage of free radionuclide in the body. The radiohalogen ²¹¹At accumulates in various tissues, with specifically high uptake in the thyroid. When normal thyroid function is disturbed because of ionizing radiation (IR) exposure, deleterious effects can occur in tissues that depend on thyroid hormone (TH) regulation for normal physiologic function. However, knowledge of systemic effects is still rudimentary. We previously reported similarities in transcriptomic regulation between the thyroid and other tissues despite large differences in absorbed dose from ²¹¹At. Here, we present supportive evidence on systemic effects after ²¹¹At administration.

METHODS

Expression microarray data from the kidney cortex and medulla, liver, lungs, and spleen were used from previous studies in which mice were intravenously injected with 0.064-42 kBq of ²¹¹At and killed after 24 h or injected with 1.7 kBq of ²¹¹At and killed after 1, 6, or 168 h. Controls were mock-treated and killed after 24 h. Literature-based gene signatures were used to evaluate the relative impact from IR- or TH-induced regulation. Thyroid- and TH-associated upstream regulators as well as thyroid-related diseases and functions were generated using functional analysis software.

RESULTS

Responses in IR- or TH-associated gene signatures were tissue-specific and varied over time, and the relative impact of each gene signature differed between the investigated tissues. The liver showed a clear dominance of TH-responding genes. In the kidney cortex, kidney medulla, and lungs, the TH-associated signature was detected to at least an extent similar to the IR-associated signature. The spleen was the single tissue showing regulation of only IR-associated signature genes. Various thyroid-associated diseases and functions were inferred from the data: L-triiodothyronine, TH, TH receptor, and triiodothyronine (reverse) were inferred as upstream regulators with differences in incidence and strength of regulation depending on tissue type.

CONCLUSION

These findings indicate that transcriptional regulation in various nonthyroid tissues was-in part-induced by thyroid (hormone)-dependent signaling. Consideration of the systemic context between tissues could contribute to normal tissue risk assessment and planning of remedial measures.

Gene expression signature in mouse thyroid tissue after (131)I and (211)At exposure

BACKGROUND

(131)I and (211)At are used in nuclear medicine and accumulate in the thyroid gland and may impact normal thyroid function. The aim of this study was to determine transcriptional profile variations, assess the impact on cellular activity, and identify genes with biomarker properties in thyroid tissue after (131)I and (211)At administration in mice.

METHODS

To further investigate thyroid tissue transcriptional responses to (131)I and (211)At administration, we generated a new transcriptional dataset that includes re-evaluated raw intensity values from our previous (131)I and (211)At studies. Differential transcriptional profiles were identified by comparing treated and mock-treated samples using Nexus Expression 3.0 software. Further data analysis was performed using R/Bioconductor and IPA.

RESULTS

A total of 1144 genes were regulated. Hierarchical clustering subdivided the groups into two clusters containing the lowest and highest absorbed dose levels, respectively, and revealed similar transcriptional regulation patterns for many kallikrein-related genes. Twenty-seven of the 1144 genes were recurrently regulated after (131)I and (211)At exposure and divided into six clusters. Several signalling pathways were affected, including calcium, integrin-linked kinase, and thyroid cancer signalling, and the peroxisomal proliferator-activated receptor network.

CONCLUSIONS

Substantial changes in transcriptional regulation were shown in (131)I and (211)At-treated samples, and 27 genes were identified as potential biomarkers for (131)I and (211)At exposure. Clustering revealed distinct differences between transcriptional profiles of both similar and different exposures, demonstrating the necessity for better understanding of radiation-induced effects on cellular activity. Additionally, ionizing radiation-induced changes in kallikrein gene expression and identified canonical pathways should be further assessed.