Emmanuel Salinas-Miranda1,2, Gerard M Healy1,2,3, Barbara Grünwald4,5, Rahi Jain6, Dominik Deniffel1, Grainne M O'Kane5,7, Robert Grant5,7, Julie Wilson5, Jennifer Knox5,7, Steven Gallinger5,7,8, Sandra Fischer4, Rama Khokha9, Masoom A Haider10,11,12,13. 1. Lunenfeld Tanenbaum Research Institute, Sinai Health System, Mount Sinai Hospital, Joseph & Wolf Lebovic Health Complex, 600 University Avenue, 6th Floor, Office 6 200, Toronto, ON, M5G 1X5, Canada. 2. Joint Department of Medical Imaging, University Health Network/Sinai Health System, 600 University Ave, 5th Floor, Toronto, ON, M5G1X5, Canada. 3. Department of Medical Imaging, University of Toronto, 263 McCaul St 4th Floor, Toronto, ON, M5T 1W5, Canada. 4. Department of Pathology, University Health Network, 610 University Ave, Toronto, ON, M5G 2C1, Canada. 5. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, 661 University Avenue, Suite 510, Toronto, ON, M5G 0A3, Canada. 6. Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, 610 University Ave, Toronto, ON, M5G 2C1, Canada. 7. Department of Medical Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, 610 University Ave, Toronto, ON, M5G 2C1, Canada. 8. Hepatobiliary Pancreatic Surgical Oncology Program, University Health Network, 190 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada. 9. Department of Medical Biophysics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, 610 University Ave, Toronto, ON, M5G 2C1, Canada. 10. Lunenfeld Tanenbaum Research Institute, Sinai Health System, Mount Sinai Hospital, Joseph & Wolf Lebovic Health Complex, 600 University Avenue, 6th Floor, Office 6 200, Toronto, ON, M5G 1X5, Canada. m.haider@utoronto.ca. 11. Joint Department of Medical Imaging, University Health Network/Sinai Health System, 600 University Ave, 5th Floor, Toronto, ON, M5G1X5, Canada. m.haider@utoronto.ca. 12. Department of Medical Imaging, University of Toronto, 263 McCaul St 4th Floor, Toronto, ON, M5T 1W5, Canada. m.haider@utoronto.ca. 13. PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, 661 University Avenue, Suite 510, Toronto, ON, M5G 0A3, Canada. m.haider@utoronto.ca.
Abstract
OBJECTIVES: Transcriptional classifiers (Bailey, Moffitt and Collison) are key prognostic factors of pancreatic ductal adenocarcinoma (PDAC). Among these classifiers, the squamous, basal-like, and quasimesenchymal subtypes overlap and have inferior survival. Currently, only an invasive biopsy can determine these subtypes, possibly resulting in treatment delay. This study aimed to investigate the association between transcriptional subtypes and an externally validated preoperative CT-based radiomic prognostic score (Rad-score). METHODS: We retrospectively evaluated 122 patients who underwent resection for PDAC. All treatment decisions were determined at multidisciplinary tumor boards. Tumor Rad-score values from preoperative CT were dichotomized into high or llow categories. The primary endpoint was the correlation between the transcriptional subtypes and the Rad-score using multivariable linear regression, adjusting for clinical and histopathological variables (i.e., tumor size). Prediction of overall survival (OS) was secondary endpoint. RESULTS: The Bailey transcriptional classifier significantly associated with the Rad-score (coefficient = 0.31, 95% confidence interval [CI]: 0.13-0.44, p = 0.001). Squamous subtype was associated with high Rad-scores while non-squamous subtype was associated with low Rad-scores (adjusted p = 0.03). Squamous subtype and high Rad-score were both prognostic for OS at multivariable analysis with hazard ratios (HR) of 2.79 (95% CI: 1.12-6.92, p = 0.03) and 4.03 (95% CI: 1.42-11.39, p = 0.01), respectively. CONCLUSIONS: In patients with resectable PDAC, an externally validated prognostic radiomic model derived from preoperative CT is associated with the Bailey transcriptional classifier. Higher Rad-scores were correlated with the squamous subtype, while lower Rad-scores were associated with the less lethal subtypes (immunogenic, ADEX, pancreatic progenitor). KEY POINTS: • The transcriptional subtypes of PDAC have been shown to have prognostic importance but they require invasive biopsy to be assessed. • The Rad-score radiomic biomarker, which is obtained non-invasively from preoperative CT, correlates with the Bailey squamous transcriptional subtype and both are negative prognostic biomarkers. • The Rad-score is a promising non-invasive imaging biomarker for personalizing neoadjuvant approaches in patients undergoing resection for PDAC, although additional validation studies are required.
OBJECTIVES: Transcriptional classifiers (Bailey, Moffitt and Collison) are key prognostic factors of pancreatic ductal adenocarcinoma (PDAC). Among these classifiers, the squamous, basal-like, and quasimesenchymal subtypes overlap and have inferior survival. Currently, only an invasive biopsy can determine these subtypes, possibly resulting in treatment delay. This study aimed to investigate the association between transcriptional subtypes and an externally validated preoperative CT-based radiomic prognostic score (Rad-score). METHODS: We retrospectively evaluated 122 patients who underwent resection for PDAC. All treatment decisions were determined at multidisciplinary tumor boards. Tumor Rad-score values from preoperative CT were dichotomized into high or llow categories. The primary endpoint was the correlation between the transcriptional subtypes and the Rad-score using multivariable linear regression, adjusting for clinical and histopathological variables (i.e., tumor size). Prediction of overall survival (OS) was secondary endpoint. RESULTS: The Bailey transcriptional classifier significantly associated with the Rad-score (coefficient = 0.31, 95% confidence interval [CI]: 0.13-0.44, p = 0.001). Squamous subtype was associated with high Rad-scores while non-squamous subtype was associated with low Rad-scores (adjusted p = 0.03). Squamous subtype and high Rad-score were both prognostic for OS at multivariable analysis with hazard ratios (HR) of 2.79 (95% CI: 1.12-6.92, p = 0.03) and 4.03 (95% CI: 1.42-11.39, p = 0.01), respectively. CONCLUSIONS: In patients with resectable PDAC, an externally validated prognostic radiomic model derived from preoperative CT is associated with the Bailey transcriptional classifier. Higher Rad-scores were correlated with the squamous subtype, while lower Rad-scores were associated with the less lethal subtypes (immunogenic, ADEX, pancreatic progenitor). KEY POINTS: • The transcriptional subtypes of PDAC have been shown to have prognostic importance but they require invasive biopsy to be assessed. • The Rad-score radiomic biomarker, which is obtained non-invasively from preoperative CT, correlates with the Bailey squamous transcriptional subtype and both are negative prognostic biomarkers. • The Rad-score is a promising non-invasive imaging biomarker for personalizing neoadjuvant approaches in patients undergoing resection for PDAC, although additional validation studies are required.
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