Limits...
Serial analysis of 38 proteins during the progression of human breast tumor in mice using an antibody colocalization microarray.

Li H, Bergeron S, Annis MG, Siegel PM, Juncker D - Mol. Cell Proteomics (2015)

Bottom Line: The profiles of 38 proteins detected in sera from these animals were analyzed by clustering, and we identified 10 proteins with the greatest relative increase in serum concentration that correlated with growth of the primary mammary tumor.Next, the sensitivity and specificity of individual and optimal protein panels were calculated, showing high accuracy as early as week 2.These results provide a foundation for studies of tumor growth through measuring serial changes of protein concentration in animal models.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Biomedical Engineering Department, §McGill University and Genome Quebec Innovation Centre.

Show MeSH

Related in: MedlinePlus

ROC curves of the 10-protein panel and six individual proteins at each time point after cancer cell injection using the self-referenced differential method. Some curves with AUC = 1 are invisible due to overlap with other curves. Unlike for the absolute threshold, no ROC curves were plotted for weeks −1 and 0 because they are not meaningful.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4390249&req=5

Figure 6: ROC curves of the 10-protein panel and six individual proteins at each time point after cancer cell injection using the self-referenced differential method. Some curves with AUC = 1 are invisible due to overlap with other curves. Unlike for the absolute threshold, no ROC curves were plotted for weeks −1 and 0 because they are not meaningful.

Mentions: For the diagnosis and monitoring of recurrence, the differential change in concentration (sometimes also called the velocity (1)) is often more accurate. Indeed, this measure intrinsically takes into account personal variation and defines individual baselines. Here, we wanted to test whether differential, self-referred diagnosis would outperform diagnosis relying on a population average-based threshold in mouse cancer models. The ROC curves of the 10 individual proteins as well as of the linear combination of the normalized variation of the 10 proteins for each time point are plotted. The ROC curves calculated using absolute and differential methods for the six proteins that linearly correlated with tumor burden are shown in Figs. 5 and 6. The ROC curves for the four proteins that increased but fluctuated are shown in supplemental Figs. 2 and 3. The AUC shows that diagnostic accuracy for all the proteins increased progressively during the time course of tumor growth as might be expected for these mouse models. The low AUC values for mouse from weeks 0 and −1 using the absolute threshold method indicate that the results reflects a change in the mouse except for TNF-RI where already a high AUC values arises before; this may be due to a measurement artifact or a coincidental higher expression in the specific subset of mice. For most proteins, the differential method and the absolute threshold analysis yielded a similar diagnostic accuracy. Using the differential method, IL-8 achieved the best performance of AUC = 1 for all the time points after injection of cancer cells, which is also reflected in its time course curves for each individual mouse shown in Fig. 3. Interestingly, the AUC already reaches a high value after only 2 weeks. For example, in week 2, MMP-3 and IL-8 show an AUC = 1 with absolute and differential methods, respectively (supplemental Figs. 2 and 3).


Serial analysis of 38 proteins during the progression of human breast tumor in mice using an antibody colocalization microarray.

Li H, Bergeron S, Annis MG, Siegel PM, Juncker D - Mol. Cell Proteomics (2015)

ROC curves of the 10-protein panel and six individual proteins at each time point after cancer cell injection using the self-referenced differential method. Some curves with AUC = 1 are invisible due to overlap with other curves. Unlike for the absolute threshold, no ROC curves were plotted for weeks −1 and 0 because they are not meaningful.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4390249&req=5

Figure 6: ROC curves of the 10-protein panel and six individual proteins at each time point after cancer cell injection using the self-referenced differential method. Some curves with AUC = 1 are invisible due to overlap with other curves. Unlike for the absolute threshold, no ROC curves were plotted for weeks −1 and 0 because they are not meaningful.
Mentions: For the diagnosis and monitoring of recurrence, the differential change in concentration (sometimes also called the velocity (1)) is often more accurate. Indeed, this measure intrinsically takes into account personal variation and defines individual baselines. Here, we wanted to test whether differential, self-referred diagnosis would outperform diagnosis relying on a population average-based threshold in mouse cancer models. The ROC curves of the 10 individual proteins as well as of the linear combination of the normalized variation of the 10 proteins for each time point are plotted. The ROC curves calculated using absolute and differential methods for the six proteins that linearly correlated with tumor burden are shown in Figs. 5 and 6. The ROC curves for the four proteins that increased but fluctuated are shown in supplemental Figs. 2 and 3. The AUC shows that diagnostic accuracy for all the proteins increased progressively during the time course of tumor growth as might be expected for these mouse models. The low AUC values for mouse from weeks 0 and −1 using the absolute threshold method indicate that the results reflects a change in the mouse except for TNF-RI where already a high AUC values arises before; this may be due to a measurement artifact or a coincidental higher expression in the specific subset of mice. For most proteins, the differential method and the absolute threshold analysis yielded a similar diagnostic accuracy. Using the differential method, IL-8 achieved the best performance of AUC = 1 for all the time points after injection of cancer cells, which is also reflected in its time course curves for each individual mouse shown in Fig. 3. Interestingly, the AUC already reaches a high value after only 2 weeks. For example, in week 2, MMP-3 and IL-8 show an AUC = 1 with absolute and differential methods, respectively (supplemental Figs. 2 and 3).

Bottom Line: The profiles of 38 proteins detected in sera from these animals were analyzed by clustering, and we identified 10 proteins with the greatest relative increase in serum concentration that correlated with growth of the primary mammary tumor.Next, the sensitivity and specificity of individual and optimal protein panels were calculated, showing high accuracy as early as week 2.These results provide a foundation for studies of tumor growth through measuring serial changes of protein concentration in animal models.

View Article: PubMed Central - PubMed

Affiliation: From the ‡Biomedical Engineering Department, §McGill University and Genome Quebec Innovation Centre.

Show MeSH
Related in: MedlinePlus