Evaluation of Lung Cancer Patient Response to First-Line Chemotherapy by Integration of Tumor Core Biopsy Metabolomics with Multiscale Modeling

Abstract

The standard of care for intermediate (Stage II) and advanced (Stages III and IV) non-small cell lung cancer (NSCLC) involves chemotherapy with taxane/platinum derivatives, with or without radiation. Ideally, patients would be screened a priori to allow non-responders to be initially treated with second-line therapies. This evaluation is non-trivial, however, since tumors behave as complex multiscale systems. To address this need, this study employs a multiscale modeling approach to evaluate first-line chemotherapy response of individual patient tumors based on metabolomic analysis of tumor core biopsies obtained during routine clinical evaluation. Model parameters were calculated for a patient cohort as a function of these metabolomic profiles, previously obtained from high-resolution 2DLC-MS/MS analysis. Evaluation metrics were defined to classify patients as Disease-Control (DC) [encompassing complete-response (CR), partial-response (PR), and stable-disease (SD)] and Progressive-Disease (PD) following first-line chemotherapy. Response was simulated for each patient and compared to actual response. The results show that patient classifications were significantly separated from each other, and also when grouped as DC vs. PD and as CR/PR vs. SD/PD, by fraction of initial tumor radius metric at 6 days post simulated bolus drug injection. This study shows that patient first-line chemotherapy response can in principle be evaluated from multiscale modeling integrated with tumor tissue metabolomic data, offering a first step towards individualized lung cancer treatment prognosis.

Keywords: Chemotherapy; Computational simulation; Lung cancer; Mathematical modeling; Metabolomics; Personalized medicine.

Figure 1.

Tumor model evaluation metrics evaluated at 6 days (80 time steps) post simulated bolus drug injection. Color highlights the characteristics of each metric.

Figure 2.

Representative images of simulated tumors before and after systemic bolus drug injection. Left set: tumor with proliferating (red), hypoxic (blue) and necrotic (brown) tissues immediately before drug injection. Middle set: approximately 4.5 days after injection; Right set: approximately 9 days after injection. Capillary bed is shown as brown grid lines, with vessels growing in response to angiogenesis as irregular lines. Oxygen and lactic acid concentration are shown within the domain (non-dimensionalized by maximum value within the vasculature). Rows denote clinical response groups: CR = complete response; PR = partial response; SD = stable disease; PD = progressive disease.

Figure 3.

Evaluation metrics of simulated patient tumors at 6 days (80 time steps) post simulated bolus drug injection (~144hrs) for DC vs. PD, CR/PR vs. SD/PD, and CR vs. PR vs. SD vs. PD clinical groups. CR = complete response; PR = partial response; SD = stable disease; PD = progressive disease. Bars represent average value for all replicates and patients within each clinical response group and error bars represent standard deviation (n=12). *P ≤ 0.1; **P ≤ 0.05; ***P ≤ 0.01.

Figure 4.

Model simulated response for each patient sample was sorted by final fraction of initial radius evaluation metric (horizontal axis), with smaller radius indicating favorable response and larger radius being unfavorable. Samples were labeled according to the ordinal nature of the RECIST guideline classifications (vertical axis) with CR (green) representing the most responsive tumors and PD (red) representing the least responsive tumors, while PR and SD (orange) lie in between.

Figure 5.

Correlations revealed by the patient-specific simulations between model evaluation metrics and the metabolomic data. Blank cells indicate no significant correlation.