Modelling the impact of tumour hypoxia on proton therapy and concurrent chemotherapy on locally advanced pancreatic cancer—insights from an <i>in silico</i> study

<i>Objective.</i>Pancreatic adenocarcinoma (PDAC) is notoriously difficult to treat due to treatment-resistance and the pancreas' proximity to organs at risks (OARs). Tumour hypoxia further complicates treatment, with substantial intra- and inter-tumour heterogeneity limiting predictability of treatment response, and often requiring multimodal therapy. Proton beam therapy (PBT) with concurrent chemotherapy has been proposed as a promising alternative for patients with locally-advanced unresectable disease. This study aims to evaluate the impact of tumour hypoxia on PBT outcomes in PDAC, and whether concurrent chemotherapy can offset hypoxia-related reductions in local control.<i>Approach.</i>Thirty PBT treatment plans from previous work were utilised. An<i>in silico</i>model was developed to generate multiple hypoxia scenarios within plausible bounds reported in literature on PDAC. The effect of intra-fraction reoxygenation was modelled, followed by the addition of concurrent gemcitabine-based chemotherapy from clinical data. For each scenario, three-dimensional distributions of biologically effective dose, survival fraction, and tumour control probability were evaluated.<i>Main results.</i>Tumour hypoxia significantly reduced the weighted average TCP in larger internal target volumes, particularly where PBT dose was constrained by proximity to OARs. Intra-fraction reoxygenation improved TCP by up to 13.4% [95%CI:6.5, 20.4], and was most effective in tumours with high-grade hypoxia and dose-limited regions. Chemotherapy improved TCP by up to 21.9% [95%CI:20.1, 26.2], though its benefit mitigated dose-loss due to nearby OARs rather than directly mitigating hypoxia.<i>Significance.</i>These findings highlight the importance of considering hypoxia and spatial dose limitations when evaluating treatment efficacy with PBT. Quantifying tumour hypoxia and reoxygenation dynamics before and during treatment could offer insight into local control outcomes. Concurrent chemotherapy can enhance tumour control, but its effect is more influenced by surrounding anatomy than hypoxia, suggesting that while it improves local control, it is insufficient as a standalone treatment for locally-advanced PDAC.

Authors

Institutions

Publication Details

Journal
Physics in Medicine and Biology
Published
2025-12-02
DOI
https://doi.org/10.1088/1361-6560/ae273b
Primary Topic
Cancer, Hypoxia, and Metabolism
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling the impact of tumour hypoxia on proton therapy and concurrent chemotherapy on locally advanced pancreatic cancer—insights from an in silico study

Eva Bezak, Puthenparampil Wilson, Peter Gorayski, Melissa McIntyre
Physics in Medicine and Biology
Cancer, Hypoxia, and Metabolism
article

Modelling the impact of tumour hypoxia on proton therapy and concurrent chemotherapy on locally advanced pancreatic cancer—insights from an in silico study

Eva Bezak, Puthenparampil Wilson, Peter Gorayski, Melissa McIntyre
article en

Abstract

<i>Objective.</i>Pancreatic adenocarcinoma (PDAC) is notoriously difficult to treat due to treatment-resistance and the pancreas' proximity to organs at risks (OARs). Tumour hypoxia further complicates treatment, with substantial intra- and inter-tumour heterogeneity limiting predictability of treatment response, and often requiring multimodal therapy. Proton beam therapy (PBT) with concurrent chemotherapy has been proposed as a promising alternative for patients with locally-advanced unresectable disease. This study aims to evaluate the impact of tumour hypoxia on PBT outcomes in PDAC, and whether concurrent chemotherapy can offset hypoxia-related reductions in local control.<i>Approach.</i>Thirty PBT treatment plans from previous work were utilised. An<i>in silico</i>model was developed to generate multiple hypoxia scenarios within plausible bounds reported in literature on PDAC. The effect of intra-fraction reoxygenation was modelled, followed by the addition of concurrent gemcitabine-based chemotherapy from clinical data. For each scenario, three-dimensional distributions of biologically effective dose, survival fraction, and tumour control probability were evaluated.<i>Main results.</i>Tumour hypoxia significantly reduced the weighted average TCP in larger internal target volumes, particularly where PBT dose was constrained by proximity to OARs. Intra-fraction reoxygenation improved TCP by up to 13.4% [95%CI:6.5, 20.4], and was most effective in tumours with high-grade hypoxia and dose-limited regions. Chemotherapy improved TCP by up to 21.9% [95%CI:20.1, 26.2], though its benefit mitigated dose-loss due to nearby OARs rather than directly mitigating hypoxia.<i>Significance.</i>These findings highlight the importance of considering hypoxia and spatial dose limitations when evaluating treatment efficacy with PBT. Quantifying tumour hypoxia and reoxygenation dynamics before and during treatment could offer insight into local control outcomes. Concurrent chemotherapy can enhance tumour control, but its effect is more influenced by surrounding anatomy than hypoxia, suggesting that while it improves local control, it is insufficient as a standalone treatment for locally-advanced PDAC.

Physics in Medicine and BiologyVol. 70(24)
Royal Adelaide Hospital (AU), University of South Australia (AU), SA Health (AU), The University of Adelaide (AU)
Openalex Percentile: Top 53%
Cancer, Hypoxia, and Metabolism
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.