Jeroen Buijsen1, Ruud G van Stiphout2, Paul P C A Menheere3, Guido Lammering2, Philippe Lambin2. 1. Dept. of Radiation Oncology (MAASTRO Clinic), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre, The Netherlands. Electronic address: jeroen.buijsen@maastro.nl. 2. Dept. of Radiation Oncology (MAASTRO Clinic), GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre, The Netherlands. 3. Dept. of Clinical Chemistry, Maastricht University Medical Center, The Netherlands.
Abstract
PURPOSE/ OBJECTIVE: Chemoradiation (CRT) has been shown to lead to downsizing of an important portion of rectal cancers. In order to tailor treatment at an earlier stage during treatment, predictive models are being developed. Adding blood biomarkers may be attractive for prediction, as they can be collected very easily and determined with excellent reproducibility in clinical practice. The hypothesis of this study was that blood biomarkers related to tumor load, hypoxia and inflammation can help to predict response to CRT in rectal cancer. MATERIAL/ METHODS: 295 patients with locally advanced rectal cancer who were planned to undergo CRT were prospectively entered into a biobank protocol (NCT01067872). Blood samples were drawn before start of CRT. Nine biomarkers were selected, based on a previously defined hypothesis, and measured in a standardized way by a certified lab: CEA, CA19-9, LDH, CRP, IL-6, IL-8, CA IX, osteopontin and 25-OH-vitamin D. Outcome was analyzed in two ways: pCR vs. non-pCR and responders (defined as ypT0-2N0) vs. non-responders (all other ypTN stages). RESULTS: 276 patients could be analyzed. 20.7% developed a pCR and 47.1% were classified as responders. In univariate analysis CEA (p=0.001) and osteopontin (p=0.012) were significant predictors for pCR. Taking response as outcome CEA (p<0.001), IL-8 (p<0.001) and osteopontin (p=0.004) were significant predictors. In multivariate analysis CEA was the strongest predictor for pCR (OR 0.92, p=0.019) and CEA and IL-8 predicted for response (OR 0.97, p=0.029 and OR 0.94, p=0.036). The model based on biomarkers only had an AUC of 0.65 for pCR and 0.68 for response; the strongest model included clinical data, PET-data and biomarkers and had an AUC of 0.81 for pCR and 0.78 for response. CONCLUSION: CEA and IL-8 were identified as predictive biomarkers for tumor response and PCR after CRT in rectal cancer. Incorporation of these blood biomarkers leads to an additional accuracy of earlier developed prediction models using clinical variables and PET-information. The new model could help to an early adaptation of treatment in rectal cancer patients.
PURPOSE/ OBJECTIVE: Chemoradiation (CRT) has been shown to lead to downsizing of an important portion of rectal cancers. In order to tailor treatment at an earlier stage during treatment, predictive models are being developed. Adding blood biomarkers may be attractive for prediction, as they can be collected very easily and determined with excellent reproducibility in clinical practice. The hypothesis of this study was that blood biomarkers related to tumor load, hypoxia and inflammation can help to predict response to CRT in rectal cancer. MATERIAL/ METHODS: 295 patients with locally advanced rectal cancer who were planned to undergo CRT were prospectively entered into a biobank protocol (NCT01067872). Blood samples were drawn before start of CRT. Nine biomarkers were selected, based on a previously defined hypothesis, and measured in a standardized way by a certified lab: CEA, CA19-9, LDH, CRP, IL-6, IL-8, CA IX, osteopontin and 25-OH-vitamin D. Outcome was analyzed in two ways: pCR vs. non-pCR and responders (defined as ypT0-2N0) vs. non-responders (all other ypTN stages). RESULTS: 276 patients could be analyzed. 20.7% developed a pCR and 47.1% were classified as responders. In univariate analysis CEA (p=0.001) and osteopontin (p=0.012) were significant predictors for pCR. Taking response as outcome CEA (p<0.001), IL-8 (p<0.001) and osteopontin (p=0.004) were significant predictors. In multivariate analysis CEA was the strongest predictor for pCR (OR 0.92, p=0.019) and CEA and IL-8 predicted for response (OR 0.97, p=0.029 and OR 0.94, p=0.036). The model based on biomarkers only had an AUC of 0.65 for pCR and 0.68 for response; the strongest model included clinical data, PET-data and biomarkers and had an AUC of 0.81 for pCR and 0.78 for response. CONCLUSION:CEA and IL-8 were identified as predictive biomarkers for tumor response and PCR after CRT in rectal cancer. Incorporation of these blood biomarkers leads to an additional accuracy of earlier developed prediction models using clinical variables and PET-information. The new model could help to an early adaptation of treatment in rectal cancerpatients.
Authors: Catharina M L Zegers; Frank J P Hoebers; Wouter van Elmpt; Judith A Bons; Michel C Öllers; Esther G C Troost; Daniëlle Eekers; Leo Balmaekers; Marlies Arts-Pechtold; Felix M Mottaghy; Philippe Lambin Journal: Eur J Nucl Med Mol Imaging Date: 2016-06-01 Impact factor: 9.236
Authors: Yong Joon Lee; Sat Byol Lee; Suk Kyung Beak; Yoon Dae Han; Min Soo Cho; Hyuk Hur; Kang Young Lee; Nam Kyu Kim; Byung Soh Min Journal: Sci Rep Date: 2018-05-15 Impact factor: 4.379