Neoadjuvant Therapy in Rectal Cancer - Biobanking of Preoperative Tumor Biopsies

Peter Jo, Manuel Nietert, Linda Gusky, Julia Kitz, Lena C Conradi, Annegret Müller-Dornieden, Philipp Schüler, Hendrik A Wolff, Josef Rüschoff, Philipp Ströbel, Marian Grade, Torsten Liersch, Tim Beißbarth, Michael B Ghadimi, Ulrich Sax, Jochen Gaedcke, Peter Jo, Manuel Nietert, Linda Gusky, Julia Kitz, Lena C Conradi, Annegret Müller-Dornieden, Philipp Schüler, Hendrik A Wolff, Josef Rüschoff, Philipp Ströbel, Marian Grade, Torsten Liersch, Tim Beißbarth, Michael B Ghadimi, Ulrich Sax, Jochen Gaedcke

Abstract

Translational research relies on high-quality biospecimens. In patients with rectal cancer treated preoperatively with radiochemotherapy tissue based analyses are challenging. To assess quality challenges we analyzed tissue samples taken over the last years in a multicenter setting. We retrospectively evaluated overall 197 patients of the CAO/ARO/AIO-94- and 04-trial with locally advanced rectal cancer that were biopsied preoperatively at the University Medical Center Goettingen as well as in 10 cooperating hospitals in Germany. The cellular content of tumor, mucosa, stroma, necrosis and the amount of isolated DNA and RNA as well as the RNA integrity number (RIN) as quality parameters were evaluated. A high RNA yield (p = 2.75e-07) and the content of tumor (p = 0.004) is significantly associated to high RIN-values, whereas a high content of mucosa (p = 0.07) shows a trend and a high amount of necrosis (p = 0.01) is significantly associated with RNA of poor quality. Correlating biopsies from Goettingen and the cooperating centers showed comparable tumor content results. By taking small sized biopsies we could assess a clear correlation between a good RNA quality and a high amount of RNA and tumor cells. These results also indicate that specimens collected at different centers are of comparable quality.

Figures

Figure 1. Biomaterial retrieval for a collaborative…
Figure 1. Biomaterial retrieval for a collaborative research initiative.
Figure 2. Correlation between isolated RNA yield…
Figure 2. Correlation between isolated RNA yield (μg) and RIN.
(A) Scatterplot: Pearson’s correlation coefficient (r) and due to skewedness of the data also Kendall’s rank correlation tau were depicted as measures. Kendall’s rank correlation yielded a tau of 0.3369027 and had a p-value of <5.32576097e-18. (B) Boxplot: The bimodal distribution of RIN values was the trigger to further investigate the Wilcoxon test results for the low/high RIN classes, which result here in a p-value of 2.4e–22.
Figure 3. Correlation between content of tumor…
Figure 3. Correlation between content of tumor (%) and RIN.
(A) Scatterplot: Pearson’s correlation coefficient (r) and due to skewedness of the data also Kendall’s rank correlation tau were depicted as measures. Kendall’s rank correlation yielded a tau of 0.0743838 and had a p-value of 0.07292. (B) The bimodal distribution of RIN values was the trigger to further investigate the Wilcoxon test results for the low/high RIN classes, which result here in a p-value of 0.00118.
Figure 4. Correlation between content of necrosis…
Figure 4. Correlation between content of necrosis (%) and RIN.
(A) Scatterplot: Pearson’s correlation coefficient (r) and due to skewedness of the data also Kendall’s rank correlation tau were depicted as measures. Kendall’s rank correlation yielded a tau of −0.2519935 and had a p-value of 0.0007087. (B) The bimodal distribution of RIN values was the trigger to further investigate the Wilcoxon test results for the low/high RIN classes, which result here in a p-value of 0.143.
Figure 5. Of 195 analyzed patients (matched…
Figure 5. Of 195 analyzed patients (matched to available clinical data sets) 127 patients (65.13%) (good patients) were included for further molecular analyses (tumor content > 50%, RIN > 5).
RNAlater biopsy samples not fullfilling the criterions (tumor content

Figure 6. Kaplan-Meier-Curve displaying the OS between…

Figure 6. Kaplan-Meier-Curve displaying the OS between the excluded and included patients for further molecular…

Figure 6. Kaplan-Meier-Curve displaying the OS between the excluded and included patients for further molecular analyses.
The test used was the log rank test for differences regarding survival in “excluded samples” vs “included samples” groups, which were defined by cutoffs (tumor content > 50% and RIN > 5).

Figure 7. Kaplan-Meier-Curve displaying the DFS between…

Figure 7. Kaplan-Meier-Curve displaying the DFS between the excluded and included patients for further molecular…

Figure 7. Kaplan-Meier-Curve displaying the DFS between the excluded and included patients for further molecular analyses.
The test used was the log rank test for differences regarding survival in the “excluded samples” vs “included samples” groups, which were defined by cutoffs (tumor content > 50% and RIN > 5).
All figures (7)
Figure 6. Kaplan-Meier-Curve displaying the OS between…
Figure 6. Kaplan-Meier-Curve displaying the OS between the excluded and included patients for further molecular analyses.
The test used was the log rank test for differences regarding survival in “excluded samples” vs “included samples” groups, which were defined by cutoffs (tumor content > 50% and RIN > 5).
Figure 7. Kaplan-Meier-Curve displaying the DFS between…
Figure 7. Kaplan-Meier-Curve displaying the DFS between the excluded and included patients for further molecular analyses.
The test used was the log rank test for differences regarding survival in the “excluded samples” vs “included samples” groups, which were defined by cutoffs (tumor content > 50% and RIN > 5).

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