Till sidans topp

Sidansvarig: Webbredaktion
Sidan uppdaterades: 2012-09-11 15:12

Tipsa en vän
Utskriftsversion

Deconvolution of expressi… - Göteborgs universitet Till startsida
Webbkarta
Till innehåll Läs mer om hur kakor används på gu.se

Kontaktformulär








 


OBS! Vill du ha svar, ange e-post eller telefonnummer!




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

Artikel i vetenskaplig tidskrift
Författare Britta Langen
Nils Rudqvist
Johan Spetz
Khalil Helou
Eva Forssell-Aronsson
Publicerad i Plos One
Volym 13
Nummer/häfte 7
Sidor 17
ISSN 1932-6203
Publiceringsår 2018
Publicerad vid Institutionen för kliniska vetenskaper, Avdelningen för radiofysik
Institutionen för kliniska vetenskaper, Avdelningen för onkologi
Sahlgrenska Cancer Center
Sidor 17
Språk en
Länkar dx.doi.org/10.1371/journal.pone.019...
Ämnesord gene-expression, free at-211, transcriptional responses, mouse-tissues, kidney tissue, dose-rate, c-cells, mice, radiation, i-131
Ämneskategorier Cell- och molekylärbiologi

Sammanfattning

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.

Sidansvarig: Webbredaktion|Sidan uppdaterades: 2012-09-11
Dela:

På Göteborgs universitet använder vi kakor (cookies) för att webbplatsen ska fungera på ett bra sätt för dig. Genom att surfa vidare godkänner du att vi använder kakor.  Vad är kakor?