Assessment of Patient-Derived Xenograft Growth and Antitumor Activity: The NCI PDXNet Consensus Recommendations

Abstract

Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to in vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison of different studies and determination of whether a PDX experiment has produced evidence needed to consider a new therapy promising. We present consensus recommendations for assessment of PDX growth and antitumor activity, providing public access to a suite of tools for in vivo growth analyses. We expect that harmonizing PDX study design and analysis and assessing a suite of analytical tools will enhance information exchange and facilitate identification of promising novel therapies and biomarkers for guiding cancer therapy.

Figure 1.

Different growth metrics applied to four PDX experiments. Four PDX models were subjected to daily with a drug. The growth of treated tumors (blue) and control tumors (gray) is displayed using different metrics. A, Spider plots of individual tumor volumes. Calculated as follows: Tumor volume (mm³) = [tumor length × (tumor width)²]/2B). B, Growth curves representing average tumor volumes. C, Spider plots of changes in tumor volume. Calculated as follows: % tumor volume change = ${\mathit{\Delta }}_{{\mathit{V}}_{\mathit{t}}}\mathit{=}\frac{{\mathit{V}}_{\mathit{t}}\mathit{-}{\mathit{V}}_{\mathit{0}}}{{\mathit{V}}_{\mathit{0}}}\mathit{\times }\mathit{100}$. D, Growth curves representing average changes in tumor volume. E, Waterfall plots of changes in tumor volume on day 21. Calculated at day 21 as follows: % tumor volume change = ${\mathit{\Delta }}_{{\mathit{V}}_{\mathit{t}}}\mathit{=}\frac{{\mathit{V}}_{\mathit{t}}\mathit{-}{\mathit{V}}_{\mathit{0}}}{{\mathit{V}}_{\mathit{0}}}\mathit{\times }\mathit{100}$. F, Waterfall plots of changes in tumor volume classified by response status. Objective responses: gray, PD (≥20% growth); dark blue, PR (≤30% tumor regression); light blue, stable disease (nonPD, nonPR). Scales capped at 200% to better show response range. G, Area under the tumor (AUCs) for tumor volume. The area under the tumor growth curve from baseline ${\mathit{t}}_{\mathit{0}}$ up to time t ÷ t.

Figure 2.

Additional metrics used to display tumor volume and antitumor activity. A, comparison of average changes in tumor volume. B, Log₂ proportional changes in tumor volume. C, Scaled average changes in tumor volume. The tumor volumes range from −100% (complete regression) to 100% (endpoint). Tumor volume four times the baseline volume was chosen as the maximum growth endpoint. D, Event-free Survival. EFS is defined as the time until the tumor volume increases by a multiple of $\mathit{\delta }$ or reaches a certain volume cutoff. Tumor doubling (EFS2) was selected as an event. For example, $\mathit{min}\left(\mathit{\tau }\mathit{:}{\mathit{\Delta }}_{{\mathit{V}}_{\mathit{\tau }}}\mathit{\ge }\mathit{\delta }\mathit{\times }\mathit{100}\right)$; $\mathit{\delta }\mathit{=}\mathit{1}$ corresponds to time until tumor doubles in size (EFS2).

Figure 3.

Combination therapy testing. The panels show the effects of treatment of PDXs with single agents (blue and green) and combination therapies (red). The black lines represent untreated controls. The panels on the left show changes in tumor volume and panels on the right show scaled average changes in tumor volume. A, PDX treated with two therapeutic agents which achieved limited activity as monotherapy but achieved disease stabilization in combination therapy. B, Both drugs had monotherapy antitumor activity, but the combination led to tumor regression. C, Prolonged treatment with two drugs, demonstrating greater antitumor activity with the combination. D, Prolonged treatment with two agents alone and in combination, followed by treatment cessation, helping to delineate differences in durability of antitumor activity. E, A PDX experiment in which the combination therapy had significant antitumor activity was primarily driven by one agent without potentiation of the antitumor activity by the combination. F, PDX experiment here shows limited single-agent activity for each therapy with slightly more growth inhibition with the combination but still with continued tumor growth.

Figure 4.

Comparison of the antitumor activity in four PDX models (A) waterfall plot of the average tumor volume changes at day 21. B, Graph of tumor volume T/C ratios. C, Hybrid tumor regression/growth inhibition plot of T/C ratios and tumor regression. The average percent decrease in tumor volume (TV) is shown for PDXs with tumor regression, whereas the T/C ratios are shown for PDXs with tumor growth above baseline volume (D) Log₂ fold change in tumor volumes. E, Objective response classification in different PDX models. Gray, PD (≥20% tumor growth); dark blue, PR (≤30% tumor regression); light blue, stable disease (SD; nonPD, nonPR). F, AUCs based on average tumor volumes (left) and scaled (right).