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@article{1523297, author = {Pačínková, Anna and Popovici, Vlad}, article_location = {New York}, article_number = {vol. 2019}, doi = {http://dx.doi.org/10.1155/2019/6763596}, keywords = {genomic signature; colorectal cancer; cross-platform analysis; microsatellite instability}, language = {eng}, issn = {2314-6133}, journal = {Biomed Research International}, title = {Cross-platform Data Analysis Reveals a Generic Gene Expression Signature for Microsatellite Instability in Colorectal Cancer}, url = {https://www.hindawi.com/journals/bmri/2019/6763596/}, volume = {2019}, year = {2019} }
TY - JOUR ID - 1523297 AU - Pačínková, Anna - Popovici, Vlad PY - 2019 TI - Cross-platform Data Analysis Reveals a Generic Gene Expression Signature for Microsatellite Instability in Colorectal Cancer JF - Biomed Research International VL - 2019 IS - vol. 2019 SP - 1-9 EP - 1-9 PB - Hindawi Publishing Corporation SN - 23146133 KW - genomic signature KW - colorectal cancer KW - cross-platform analysis KW - microsatellite instability UR - https://www.hindawi.com/journals/bmri/2019/6763596/ L2 - https://www.hindawi.com/journals/bmri/2019/6763596/ N2 - The dysfunction of the DNA mismatch repair system results in microsatellite instability (MSI). MSI plays a central role in the development of multiple human cancers. In colon cancer, despite being associated with resistance to 5-fluorouracil treatment, MSI is a favourable prognostic marker. In gastric and endometrial cancers, its prognostic value is not so well established. Nevertheless, recognising the MSI tumours may be important for predicting the therapeutic effect of immune checkpoint inhibitors. Several gene expression signatures were trained on microarray data sets to understand the regulatory mechanisms underlying microsatellite instability in colorectal cancer. A wealth of expression data already exists in the form of microarray data sets. However, the RNA-seq has become a routine for transcriptome analysis. A new MSI gene expression signature presented here is the first to be valid across two different platforms, microarrays and RNA-seq. In the case of colon cancer, its estimated performance was (i) AUC = 0.94, 95% CI = (0.90 - 0.97) on RNA-seq and (ii) AUC = 0.95, 95% CI = (0.92 - 0.97) on microarray. The 25-gene expression signature was also validated in two independent microarray colon cancer data sets. Despite being derived from colorectal cancer, the signature maintained good performance on RNA-seq and microarray gastric cancer data sets (AUC = 0.90, 95% CI = (0.85 - 0.94) and AUC = 0.83, 95% CI = (0.69 - 0.97), respectively). Furthermore, this classifier retained high concordance even when classifying RNA-seq endometrial cancers (AUC = 0.71, 95% CI = (0.62 - 0.81). These results indicate that the new signature was able to remove the platform-specific differences while preserving the underlying biological differences between MSI/MSS phenotypes in colon cancer samples. ER -
PAČÍNKOVÁ, Anna and Vlad POPOVICI. Cross-platform Data Analysis Reveals a Generic Gene Expression Signature for Microsatellite Instability in Colorectal Cancer. \textit{Biomed Research International}. New York: Hindawi Publishing Corporation, 2019, vol.~2019, vol. 2019, p.~1-9. ISSN~2314-6133. Available from: https://dx.doi.org/10.1155/2019/6763596.
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