Mechanical Signals Inhibit Growth of a Grafted Tumor In Vivo: Proof of Concept

In the past ten years, many studies have shown that malignant tissue has been “normalized” in vitro using mechanical signals. We apply the principles of physical oncology (or mechanobiology) in vivo to show the effect of a “constraint field” on tumor growth. The human breast cancer cell line, MDA MB 231, admixed with ferric nanoparticles was grafted subcutaneously in Nude mice. The magnetizable particles rapidly surrounded the growing tumor. Two permanent magnets located on either side of the tumor created a gradient of magnetic field. Magnetic energy is transformed into mechanical energy by the particles acting as “bioactuators”, applying a constraint field and, by consequence, biomechanical stress to the tumor. This biomechanical treatment was applied 2 hours/day during 21 days, from Day 18 to Day 39 following tumor implantation. The study lasted 74 days. Palpable tumor was measured two times a week. There was a significant in vivo difference between the median volume of treated tumors and untreated controls in the mice measured up to D 74 (D 59 + population): (529 [346; 966] mm3 vs 1334 [256; 2106] mm3; p = 0.015), treated mice having smaller tumors. The difference was not statistically significant in the group of mice measured at least to D 59 (D 59 population). On ex vivo examination, the surface of the tumor mass, measured on histologic sections, was less in the treated group, G1, than in the control groups: G2 (nanoparticles, no magnetic field), G3 (magnetic field, no nanoparticles), G4 (no nanoparticles, no magnetic field) in the D 59 population (Median left surface was significantly lower in G1 (5.6 [3.0; 42.4] mm2, p = 0.005) than in G2 (20.8 [4.9; 34.3]), G3 (16.5 [13.2; 23.2]) and G4 (14.8 [1.8; 55.5]); Median right surface was significantly lower in G1 (4.7 [1.9; 29.2] mm2, p = 0.015) than in G2 (25.0 [5.2; 55.0]), G3 (18.0 [14.6; 35.2]) and G4 (12.5 [1.5; 51.8]). There was no statistically significant difference in the day 59+ population. This is the first demonstration of the effect of stress on tumor growth in vivo suggesting that biomechanical intervention may have a high translational potential as a therapy in locally advanced tumors like pancreatic cancer or primary hepatic carcinoma for which no effective therapy is currently available.


METHODOLOGY
1. Import and Data Management: First the databases will be imported and managed to obtain and format the essential data 2. Descriptive statistics: The three variables of interest will be described, in order to check the distribution of the data and the potential presence of outliers.  Table of descriptive statistics (n, mean, std, min, max, median, Q1, Q3 and 95% Confidence Interval)  Box-plots by groups for each surface 3. Analysis (Part 1): Comparison of the treated group (G1) to the three control groups (G2, G3 and G4) for all mice in terms of Tumour volume. A one-way ANOVA (Group as unique factor, Tumour volume as response) will be performed. The tumour volume value will be taken at 59 days for mice having survived until this time and at the last measured time for the others. 4. Analysis (Part 2): Comparison of the treated group (G1) to the three control groups (G2, G3 and G4) in terms of Skin Surface and Muscle Surface. Two one-way ANOVAs (Group as unique factor, Surfaces as responses) will be performed. This will be done for all mice and then for mice having survived after 60 days.
For points 3 and 4: if a group effect is highlighted, comparisons between groups will be performed.  Pairwise comparisons between groups G2, G3 and G4 will allow us to understand if there is a significant difference between the control groups.  If so, G1 will be compared to G2, G3 and G4 separately (Dunnett test)  If not, G1 will be compared to the three groups mixed up (unadjusted t-test) The assumptions of the ANOVA will be checked:  Normality of residuals. If it is not valid, the same model will be applied to log-transformed data. If it is still invalid, a nonparametric test will be performed: A Kruskal-Wallis test will allow to test the global Group effect and then, if it is significant, Wilcoxon tests will compare groups between them.  Homogeneity of variances. If variances are not homogeneous across groups, this will be taken into account in the model.

Skin surface
The skin surface was not measured on all the tumors (insufficient quality of the cut). Total surface measurements are available for 51 tumors.

Muscle surface
The muscle surface was not measured on all the tumors (insufficient quality of the cut). Total surface measurements are available for 51 tumors.

Tumor volume
Normality of residuals is not verified with raw data (p<0.01) and also with data transformed in log (p<0.01). So a nonparametric test is performed.
The pairwise comparisons between groups G2, G3 and G4 are performed with a Wilcoxon test using a Bonferroni-Holm adjustment.

Comparison Signification (Bonferroni-Holm adjustment)
G2 vs G3 Not Significant (p=0.359) G2 vs G4 Not Significant (p=0.114) G3 vs G4 Not Significant (p=0.947) All p-values are higher than 0.05, so there is no significant difference between untreated groups. The three groups are mixed up. A Wilcoxon test is performed between Treated (G1) and Untreated (G2, G3 and G4).

On all mice
Normality of residuals is not verified with raw data (p=0.0002) but is verified with data log transformed (p=0.611) so a one-way ANOVA is performed with log-transformation.

Effect Signification (pvalue)
Group Significant (p=0.021) The first result shows that groups have an effect on skin surface. Next All p-values are higher than 0.05, so there is no significant difference between the three groups untreated. A mixed up of this 3 groups is realized.
Finally, one-way ANOVA is performed using contrast option:

On mice having survived after 60 days
Normality of residuals is not verified with raw data (p=0.002) but is verified with data log transformed (p=0.2086) so a one-way ANOVA is performed with log-transformation. Variability of group 1 is not homogenous with variabilities of the 3 others groups. So, this heterogeneity was taken into account in the model with the option "group=".

Effect Signification (pvalue)
Group Not Significant (p=0.172) On one-way anova, group effect is not significant (p=0.172). There is no significantly difference between the 4 groups on mice having survived after 60 days.

On all mice
Normality of residuals is not verified with raw data (p=0.0063) but is verified with data log transformed (p=0.937) so a one-way ANOVA is performed with log-transformation.

Effect Signification (pvalue)
Group Significant (p=0.004) The first result shows that groups have an effect on muscle surface. All p-values are higher than 0.05, so there is no significant difference between the three groups untreated. A mixed up of this 3 groups is realized.
Finally, a one-way ANOVA is performed using contrast option:

On mice having survived after 60 days
Normality of residuals is verified with raw data (p=0,10) so a one-way ANOVA is performed.

Effect Signification
Group Not Significant (p=0.093) On one-way ANOVA, group effect is not significant (p=0.093). There is no significantly difference of muscle surface between G1 and other groups on mice having survived after 60 days.