<p>We seek to establish a parsimonious mathematical framework for understanding the interaction and dynamics of the response of pancreatic cancer to the NGC triple chemotherapy regimen (mNab-paclitaxel, gemcitabine, and cisplatin), stromal-targeting drugs (calcipotriol and losartan), and an immune checkpoint inhibitor (anti-PD-L1). We developed a set of ordinary differential equations describing changes in tumor size under the influence of cocktails of treatments. Parameter estimation relies on three tumor volume measurements obtained over a 14-day period in a genetically engineered pancreatic cancer model (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41540_2025_593_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="324" /> </InlineMediaObject> <EquationSource Format="TEX">${{Kras}}^{{\rm{LSL}}-{\rm{G12D}}}\,;\,{{Trp53}}^{{\rm{LSL}}-{\rm{R172H}}}\,;\,{Pdx1}-{\rm{Cre}}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mrow> <mi>K</mi> <mi>r</mi> <mi>a</mi> <mi>s</mi> </mrow> <mrow> <mstyle mathvariant="normal"> <mi>L</mi> <mi>S</mi> <mi>L</mi> </mstyle> <mo>-</mo> <mstyle mathvariant="normal"> <mi>G</mi> <mn>12</mn> <mi>D</mi> </mstyle> </mrow> </msup> <mspace width="0.25em" /> <mo>;</mo> <mspace width="0.25em" /> <msup> <mrow> <mi>T</mi> <mi>r</mi> <mi>p</mi> <mn>53</mn> </mrow> <mrow> <mstyle mathvariant="normal"> <mi>L</mi> <mi>S</mi> <mi>L</mi> </mstyle> <mo>-</mo> <mstyle mathvariant="normal"> <mi>R</mi> <mn>172</mn> <mi>H</mi> </mstyle> </mrow> </msup> <mspace width="0.25em" /> <mo>;</mo> <mspace width="0.25em" /> <mi>P</mi> <mi>d</mi> <mi>x</mi> <mn>1</mn> <mo>-</mo> <mstyle mathvariant="normal"> <mi>C</mi> <mi>r</mi> <mi>e</mi> </mstyle> </mrow> </math></EquationSource> </InlineEquation>). Our model reproduces tumor growth in all scenarios with an average concordance correlation coefficient (CCC) of 0.99 ± 0.01. We conduct leave-one-out predictions (average CCC = 0.74 ± 0.06), mouse-specific predictions (average CCC = 0.75 ± 0.02), and hybrid, group-informed, mouse-specific predictions (average CCC = 0.85 ± 0.04). The developed mathematical model demonstrates high accuracy in fitting the experimental tumor data and a robust ability to predict tumor response to treatment. This approach has important implications for optimizing combination NGC treatment strategies.</p>

Modeling tumor dynamics and predicting response to therapies in a murine pancreatic cancer model

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2025年11月4日

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Krithik Vishwanath,
Hoon Choi,
Mamta Gupta,
Rong Zhou,
Anna G. Sorace,
Thomas E. Yankeelov,
Ernesto A. B. F. Lima

摘要

We seek to establish a parsimonious mathematical framework for understanding the interaction and dynamics of the response of pancreatic cancer to the NGC triple chemotherapy regimen (mNab-paclitaxel, gemcitabine, and cisplatin), stromal-targeting drugs (calcipotriol and losartan), and an immune checkpoint inhibitor (anti-PD-L1). We developed a set of ordinary differential equations describing changes in tumor size under the influence of cocktails of treatments. Parameter estimation relies on three tumor volume measurements obtained over a 14-day period in a genetically engineered pancreatic cancer model ( ${{Kras}}^{{\rm{LSL}}-{\rm{G12D}}}\,;\,{{Trp53}}^{{\rm{LSL}}-{\rm{R172H}}}\,;\,{Pdx1}-{\rm{Cre}}$ ${K r a s}^{L S L - G 12 D}; {T r p 53}^{L S L - R 172 H}; P d x 1 - C r e$ ). Our model reproduces tumor growth in all scenarios with an average concordance correlation coefficient (CCC) of 0.99 ± 0.01. We conduct leave-one-out predictions (average CCC = 0.74 ± 0.06), mouse-specific predictions (average CCC = 0.75 ± 0.02), and hybrid, group-informed, mouse-specific predictions (average CCC = 0.85 ± 0.04). The developed mathematical model demonstrates high accuracy in fitting the experimental tumor data and a robust ability to predict tumor response to treatment. This approach has important implications for optimizing combination NGC treatment strategies.