Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation.

Frontiers in oncology(2023)

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摘要
The 5-segment model associated C-3SFBP marker with the most-RS and C-7IUVU marker with the most-RR cell strains. Both markers were mapped to gene regions (MCC and SLC1A6, respectively). In addition, C-3SFBP marker is also located in enhancer and multiple binding motifs. Moreover, for most CNVs significantly correlated with SF2, the radiosensitivity increased with the copy-number decrease.In conclusion, the DP-based piecewise multivariate linear regression method helps narrow the set of CNV markers from the whole radiosensitivity range to the smaller intervals of interest. Notably, SF2 partitioning not only improves the SF2 estimation but also provides distinctive markers. Ultimately, segment-related markers can be used, potentially with tissues' specific factors or other clinical data, to identify radiotherapy patients who are most RS and require reduced doses to avoid complications and the most RR eligible for dose escalation to improve outcomes.
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关键词
radiosensitivity, surviving fraction at 2 Gy (SF2), dynamic programming, linear regression, Affymetrix CytoScan HD microarrays, copy number variation (CNV), radiogenomics
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