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- Dalmo, Johanna, et al.
(författare)
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Biodistribution of 177Lu-octreotate and 111In-minigastrin in female nude mice transplanted with human medullary thyroid carcinoma GOT2.
- 2012
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Ingår i: Oncology reports. - : Spandidos Publications. - 1791-2431 .- 1021-335X. ; 27:1, s. 174-181
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Tidskriftsartikel (refereegranskat)abstract
- To be able to evaluate new radiopharmaceuticals and optimize diagnostic and therapeutic procedures, relevant animal models are required. The aim of this study was to evaluate the medullary thyroid carcinoma GOT2 animal model by analyzing the biodistribution of 177Lu-octreotate and 111In-minigastrin (MG0). BALB/c nude mice, subcutaneously transplanted with GOT2, were intravenously injected with either 177Lu-octreotate or 111In-MG0, with or without excess of unlabeled human minigastrin simultaneously with 111In-MG0. Animals were sacrificed 1-7 days after injection in the 177Lu-octreotate study and 1 h after injection of 111In-MG0. The activity concentrations in organs and tissues were determined and mean absorbed doses from 177Lu were calculated. There was a specific tumor uptake of either 177Lu-octreotate or 111In-MG0. 177Lu-octreotate samples showed high activity concentrations in tissues expressing somatostatin receptors (SSTR). For both radiopharmaceuticals the highest activity concentrations were found in the kidneys. Compared to results from similar studies in mice with another MTC cell line (TT) the biodistribution was favorable (higher tumor uptake) for the GOT2 model, while compared to other animal models expressing SSTR, the tumor uptake of 177Lu-octreotate was modest. In conclusion, the GOT2 animal model is a valuable model for evaluation and optimization of diagnostic and therapeutic procedures using radiolabeled somatostatin, CCK2 and gastrin analogues prior to clinical studies.
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- Langen, Britta, et al.
(författare)
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Data convolution and circadian rhythm impact identification of biomarker genes for ionizing radiation exposure in vivo: concept study on 131I exposure in mouse thyroid
- 2015
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Ingår i: 15th International Congress of Radiation Research, Kyoto, Japan, May 25-29.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Background: Expression microarrays have been used increasingly for biomarker discovery of genes related to ionizing radiation (IR) exposure, particularly in vivo. However, diurnal variation of gene expression and data convolution from mixed cell populations can hinder biomarker discovery. For one, candidate biomarker genes may underlie circadian rhythmicity and their expression may oscillate affecting their robustness or indicative potential. For the other, significant responses from a specific cell type can be hidden in expression data from mixed cell populations creating bias in results or even precluding biomarker discovery. Aim: To identify biomarkers of IR exposure in thyroid tissue and asses their robustness with regard to circadian rhythm and data convolution. Methods: Female BALB/c nude mice (n=3–4/group) were i.v. injected with 90 kBq 131I, or mock-treated, at 9am, 12pm, or 3pm and killed after 24h. Total RNA was extracted from excised thyroids and subjected to microarray analysis (Illumina platform). Data were processed with Nexus Expression v3.0 (cut-off adjusted P <0.01; log2 ratio ≥0.58). Enriched biological processes (P value <0.05) were categorized after cellular function according to Gene Ontology terms. Data was deconvoluted by cell frequency of follicular cells and C-cells with csSAM using R/Bioconductor. Thyroid mean absorbed dose was calculated as 5.9 Gy using the MIRD formalism. Results: Twenty-five genes responded to 131I in thyroid irrespective of time of day, notably members of the kallikrein (KLK1) gene family, but direction of regulation and fold-change differed distinctly. All KLK1 transcripts were detected in at least one deconvoluted data set, while five additional KLK1 transcripts were detected upon deconvolution. Deconvolution also increased the detection rate of significant transcript regulation and regulated biological processes: DNA integrity, gene expression integrity, and cellular stress were negative in convoluted data, but showed distinct responses in both follicular cells and C-cells. Conclusions: The KLK1 gene family is a promising biomarker candidate that shows robustness of detection. Circadian rhythm and convolution affected the quality and quantity of detected transcriptional responses and we advocate their consideration in the in vivo setting.
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- Langen, Britta, et al.
(författare)
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Deconvolution of expression microarray data reveals I-131-induced responses otherwise undetected in thyroid tissue
- 2018
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Ingår i: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 13:7
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Tidskriftsartikel (refereegranskat)abstract
- 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 I-131 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 I-131-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.
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