Abstract
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Objectives Cancer cell-lines have contributed to our understanding of cancer biology, to drug screening, and help inform the development and validation of oncologic radiotracers. Cancer cell lines with a shorter doubling time (DT) typically have more aggressive behavior. We assessed correlations between the DTs of colon cancer cell lines and the mRNA abundance for Ki67, PCNA, TK1, thymidylate synthase (TYMS), and transporters (SLC29A1-2); likely predictors of radiotracer behavior in vivo
Methods A NCI 60 exon dataset (interrogating over 1 million exon clusters within the known and predicted transcribed regions of the entire genome) was selected from the NIH Gene Expression Omnibus which contains 178 chips including 7 colon cancer cell lines with triplicates for each. Using Partek, commercial software, we obtained the average abundance of transcripts of interest to proliferation and glycolysis radiotracers. Correlations between the abundance of genes and documented doubling times were determined (α=0.05 for a one-tailed test).
Results The correlation coefficient r of TK1 (phosphorylating FLT) vs. DTs was -0.68 (p=0.04 < 0.05=α, one-tail). The r of TYMS (de novo synthesis of thymidine) vs. DTs was -0.65 (p=0.06). The r of Ki67 vs DTs was -0.51 (p=0.12). The r of PCNA vs. DTs was -0.02 (p=0.48). The r of SLC29A1 (ENT1, FLT transporter) vs. DTs was -0.27 (p=0.28). The r of SLC29A2 (ENT2) vs. DTs was 0.20 (p=0.33). Correlations between DTs and HK1, PKM2, or glucose transporters were not appreciated.
Conclusions The message abundance of TK1 has relatively better correlation to DTs of colon cancer cell lines than do message levels of the conventional proliferation marker Ki67, PCNA or membrane transporters for FDG or nucleosides. These correlations are negative, indicating higher TK1 abundance is associated with shorter DT. Our conclusions are consistent with in vivo data showing FLT uptake to be more related to proliferation than FDG uptake, but ideally should be confirmed with protein measurements.
Research Support NIH T32 training grant